From bruce@Think.COM  Tue Dec 18 11:49:44 1990
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From: Bruce Walker <bruce@Think.COM>
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To: Cellular-Automata@Think.COM
Subject: Cellular Automata List

This is an announcement of the resurrection of the Cellular-Automata@Think.COM
mailing list.  This list is also known as the CA-L@MITVMA list in the BITNET
world, and comp.theory.cell-automata in the inet distribution of Usenet.

I just caught up on nearly a year's worth of requests for additions and
deletions from the list.  As soon as I finish cleaning up the list, I will be
handing it over to a new maintainer, Dave Hiebeler, who has contributed much of
what has appeared on this list in the past.

This list will be archived, but the new archives will not be readily available
on the Internet until Dave and I work out a solution to that problem.  The list
is also archived on BITNET via LISTSERV@MITVMA, but those archives only go back
a year or two, and the list was dormant much of that time.

Requests to be added or deleted should go to the above LISTSERV machine if you
are on BITNET, or to Cellular-Automata-Request@Think.COM on the Internet.

Since the list has been inactive for so long, there will probably be tons of
bounced mail from obsolete addresses on the list.  I plan to weed most of them
out with this message as a test.  If you have something to contribute to the
list, you might want to wait a few days, after which you are likely to be
bothered with fewer error returns.

--Bruce Walker
  Thinking Machines Corporation, Cambridge, MA
  bruce@think.com; +1 617 234 4810


From bruce@Think.COM  Tue Dec 18 13:03:02 1990
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From: Bruce Walker <bruce@Think.COM>
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To: Cellular-Automata@Think.COM
Subject: Cellular Automata List

This is an announcement of the resurrection of the Cellular-Automata@Think.COM
mailing list.  This list is also known as the CA-L@MITVMA list in the BITNET
world, and comp.theory.cell-automata in the inet distribution of Usenet.

I just caught up on nearly a year's worth of requests for additions and
deletions from the list.  As soon as I finish cleaning up the list, I will be
handing it over to a new maintainer, Dave Hiebeler, who has contributed much of
what has appeared on this list in the past.

This list will be archived, but the new archives will not be readily available
on the Internet until Dave and I work out a solution to that problem.  The list
is also archived on BITNET via LISTSERV@MITVMA, but those archives only go back
a year or two, and the list was dormant much of that time.

Requests to be added or deleted should go to the above LISTSERV machine if you
are on BITNET, or to Cellular-Automata-Request@Think.COM on the Internet.

Since the list has been inactive for so long, there will probably be tons of
bounced mail from obsolete addresses on the list.  I plan to weed most of them
out with this message as a test.  If you have something to contribute to the
list, you might want to wait a few days, after which you are likely to be
bothered with fewer error returns.

--Bruce Walker
  Thinking Machines Corporation, Cambridge, MA
  bruce@think.com; +1 617 234 4810


From cellular-automata-request@Think.COM  Thu Dec 27 13:25:40 1990
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Date: 27 Dec 90 17:13:40 GMT
From: snorkelwacker.mit.edu!apple!netcom!cmilono@bloom-beacon.mit.edu  (Carlo Milono)
Organization: Netcom-
Subject: Cell Master
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Does anyone out on the net use Sintar Software's Cell Master?  I just got
a copy for Xmas and was so intrigued that I searched my .newsrc to find
this group.  

This program lists for $45 and is for IBM PC's only as of this writing.
It includes Conway's Life, a cell editor, a rules editor, and many simple
constructs, including a set of cells and rules that allow the construction
of a Virtual Computer.  I am in the process of making a Full Adder circuit.

The rules are:

	Conway
	Sum Values
	Euclid
	Difference
	Rotational
	Planar
	Separable
	...and Exhaustive

There is a contest to find the following:
	New Rule sets
	Still Life with a speed of zero
	Gliders
	Puffers
	Guns
	Garden Of Eden (only *you* can create this out of random chaos!)

Sintar also makes a very good fractal package and various addons to it.

	Sintar Software
	1001 4th Ave. Suite 3200
	Seattle, WA  98154
	(206) 625-1213

I would be interested in trading interesting rule sets and cell forms.

DISCLAIMER: I just like this package and want a dialog...I don't own stock
            nor do I work for Sintar or affiliates (if any).
A



-- 
+--------------------------------------------------------------------------+
|  Carlo Milono:  netcom!cmilono@apple.com   or   apple!netcom!cmilono     |
|"When a true genius appears in the world, you may know him by this sign,  |
|that the dunces are all in confederacy against him."   - Jonathan Swift   |
+--------------------------------------------------------------------------+

From cellular-automata-request@Think.COM  Thu Dec 27 23:25:42 1990
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Date: 28 Dec 90 00:53:25 GMT
From: snorkelwacker.mit.edu!hsdndev!wuarchive!zaphod.mps.ohio-state.edu!mips!daver!zorch!xanthian@bloom-beacon.mit.edu  (Kent Paul Dolan)
Organization: SF-Bay Public-Access Unix
Subject: Re: Cell Master
Message-Id: <1990Dec28.005325.27081@zorch.SF-Bay.ORG>
References: <19458@netcom.UUCP>
Sender: ca-request@Think.COM
To: ca@Think.COM

In article <19458@netcom.UUCP> cmilono@netcom.UUCP (Carlo Milono) writes:
>Does anyone out on the net use Sintar Software's Cell Master?  I just got
>a copy for Xmas and was so intrigued that I searched my .newsrc to find
>this group.  

>This program lists for $45 and is for IBM PC's only as of this writing.
>It includes Conway's Life, a cell editor, a rules editor, and many simple
>constructs, including a set of cells and rules that allow the construction
>of a Virtual Computer.  I am in the process of making a Full Adder circuit.

>The rules are:

>	Conway
>	Sum Values
>	Euclid
>	Difference
>	Rotational
>	Planar
>	Separable
>	...and Exhaustive

>There is a contest to find the following:
>	New Rule sets
>	Still Life with a speed of zero
>	Gliders
>	Puffers
>	Guns
>	Garden Of Eden (only *you* can create this out of random chaos!)

>Sintar also makes a very good fractal package and various addons to it.

>	Sintar Software
>	1001 4th Ave. Suite 3200
>	Seattle, WA  98154
>	(206) 625-1213

>I would be interested in trading interesting rule sets and cell forms.

>+--------------------------------------------------------------------------+
>|  Carlo Milono:  netcom!cmilono@apple.com   or   apple!netcom!cmilono     |
>|"When a true genius appears in the world, you may know him by this sign,  |
>|that the dunces are all in confederacy against him."   - Jonathan Swift   |
>+--------------------------------------------------------------------------+

Haven't seen the package, but I hope if the principals are watching the net
they will think of the 2,000,000 Amiga marketplace for a port.  There have
been some Life implementations done using the Amiga's bit blitter to do the
entire calculation for the screen refresh, which make it possible to run
Life at 30 generations a second in high resolution (640x400) mode!  Not too
shabby for a home computer.  I don't know much about the blitter ruleset,
so I don't know how successful one could be at programming more complex
cellular automaton rulesets into it, but it would be fun to see the results.

By the way, I _love_ your .siggie quote, and promptly stole a copy.

Kent, the man from xanth.
<xanthian@Zorch.SF-Bay.ORG> <xanthian@well.sf.ca.us>

From cellular-automata-request@Think.COM  Thu Jan 10 00:27:46 1991
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Date: 10 Jan 91 04:29:18 GMT
From: miken@wrc.unr.edu (Mike Nicholl)
Organization: DRI-WRC Reno
Subject: Request for programming help
Message-Id: <5234@tahoe.unr.edu>
Sender: ca-request@Think.COM
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I'm trying to write some CA code in Fortran and would appreciate
any help I can get (advice, references, pseudo-code, or working 
code). I am well aware that Fortran is not appropriate for CA work, 
but for what I need to do it appears to be the best choice at
the developmental stage. In particular I am having trouble with
the mechanics of hexagonal lattice structures. Any help would be
greatly appreciated. Thanks.

Mike

From cellular-automata-request@Think.COM  Thu Jan 10 08:27:46 1991
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Date: 10 Jan 91 11:13:26 GMT
From: yunes@litp.ibp.fr (Jean-Baptiste YUNES)
Organization: Institut Blaise Pascal, Paris, France
Subject: Research...
Message-Id: <3451@litp.ibp.fr>
Sender: ca-request@Think.COM
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Hello,

Is there anybody working on cellular automata ? I would communicate with
someone to exchange ideas on this subject. I've found some results on
synchronisation (FSSP).

	[JBY]

From cellular-automata-request@Think.COM  Thu Jan 10 14:51:55 1991
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Date: 10 Jan 91 11:13:26 GMT
From: yunes@litp.ibp.fr (Jean-Baptiste YUNES)
Organization: Institut Blaise Pascal, Paris, France
Subject: Research...
Message-Id: <3451@litp.ibp.fr>
Sender: ca-request@Think.COM
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Hello,

Is there anybody working on cellular automata ? I would communicate with
someone to exchange ideas on this subject. I've found some results on
synchronisation (FSSP).

	[JBY]

From cellular-automata-request@Think.COM  Thu Jan 10 19:29:39 1991
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Date: 10 Jan 91 17:56:15 GMT
From: callahan@server.cs.jhu.edu (Paul Callahan)
Subject: Questions and comments about Conway's Life (long)
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I've been reading about/experimenting with Conway's Life off and on for about 
six years or so, but I only recently obtained a copy of the latest version
of life for X-windows.  I was impressed with its speed and its unbounded 
universe (though I've thought of numerous improvements to the user interface
that would allow more structured design and careful experimentation).  In any 
case, I've finally gotten to the point where I've come up with some interesting
reactions that I haven't read about or don't remember, in any case (I do not 
fool myself by calling them "new").  

I've been dealing primarily with rake and spaceship interactions for
ease of experimentation (a rake will invariably escape before being eaten by 
even its most hellish progeny, and a spaceship is easy to redraw on the spot).
I do have a goal in mind for all of this, but I may never get around to 
completing it, and I'd like to know if its even worthwhile (i.e. has not been
done before).  I'm suspecting it has, because it's so natural, but I've never
read anything about it.

Ok.  Here's the main question: We all know Life is universal, but has anyone   
given a manageable, understandable, _explicit_ construction that proves
universality?  The literature I've read (such as _The Recursive Universe_ and
_Winning Ways_) talks about self-replicating machines, which is fascinating in 
its own right, but what I have in mind is a bit less ambitious.  All I want is
a universal Turing machine with one semi-infinite tape.  Less exciting,
perhaps, but at least something for which one could give an explicit 
construction that could be easily verified by hand.

I have an overall scheme for this construction that appears plausible.  Namely,
we define each tape cell of the Turing maching as a finite automaton using
standard glider gun interactions to compute the logic.  This includes "blank"
tape cells, which will contain an automaton in some initial configuration.
Each automaton will be a duplicate of the TM head's automaton, and its finite
memory will consist of the tape cell contents, a flag telling whether the head
is currently at that cell, and if so, the state of the head.  The tape head
will "move" when a cell turns off its "head" flag, and emits a small group of 
spaceships towards either its left or right neighbor, carrying away the state
of the head.

I think this can be made to work, with such cells being no harder to verify 
than any simple digital circuit.  The only apparent question is how to get
an infinite sequence of them.  The answer, which the reader may have 
anticipated, is to use a flotilla of sufficiently thinned-out rakes, headed
towards infinity, which leave a sequence of tape cells in their wake (much
as the breeder leaves a sequence of glider guns). 

So, the first sub-question (which I haven't read about, but may have missed),
is whether an arbitrarily thin rake is possible.  This turns out to be true.
I don't know if there is another standard method, but the following approach
works: Consider the collision of gliders from three rakes that produces a 
medium spaceship in the _same_ direction as the rake.  This ship will follow 
along to the next collision point, which will not produce a spaceship, but 
rather some stable garbage, consisting of a block and a beehive.  The block can
be cleaned up with a spaceship, and the beehive can be exploited (using another 
rake construction) to produce the same spaceship collision each time the beehive
appears.  In general, the thinning process becomes: 
 
         Every other collision point forms a beehive
     --> Every fourth collision point forms a beehive
     --> Every eighth collision point forms a beehive
     --> ...
    
To finish the thin rake, we use a construction that sends off a glider every 
time it eats a beehive.

The rakes that produce gliders every 24 turns are sufficiently thin to use as 
components of the constructions.  (I have a rake in xlife format that thins down
to sixteenths, which I could post/mail if anyone is interested.) The thinness 
grows exponentially with the size of the construction, but it is still rather 
big and clunky.  This brings me to my next question, which I think I can 
partially answer.

Suppose we want to create an arbitrary collision of two or more gliders every 
time we encounter a single glider.  Does there exist, for each such collision, 
a flotilla of spaceships to produce it from a single glider (without destroying
the spaceships).  I know that a fairly robust set of collisions can be obtained,
using glider/spaceship-spark interactions, based on some experimentation
on my own.  Two interesting interactions that both yield the same result (at
different orientations) are the following (where "*" is live, "." is dead).

         .******         .*****
         *.....*         *....*
         ......*         .....*
         *....*.         *...*.
         ..**...         ..*...
         .......         ......
         **.....         ..***.
         .**....         ..*...
         *......         ...*..

Note that in the first, the glider is going in the same direction (horizontally)
as the spaceship, while in the second, it is going in the opposite direction.
The result of the collision is three blocks, two gliders, and the following
shape (ship?):
                 **.
                 *.*
                 .**

The blocks are easily eliminated by spaceships, and the gliders are useful for
initiating other similar reactions.  (Note that if this reaction is attempted
with gliders from a rake, they must be spread fairly thin to give enough space
for the reaction.  A 120-step rake, constructed from the 20-step and 24-step
rakes, and turns out to be thin enough).  

A sequence of these interactions (with appropriate clean-up) can be made to
yield almost any sufficiently thin pattern of the above shape (and its mirror 
image).  These can be turned into gliders later on, using the following 
interaction:

      .*****.
      *....*.
      .....*.
      *...*..
      ..*....
      .......
      ..**...
      ..*.*..
      ...**..
      .......
      .......
      .......
      .****..
      ******.
      ****.**
      ....**.

This reaction is (relatively) quick, and requires no cleanup.  The advantage to
being able to turn a stable shape into a glider is that timing problems in
glider collisions are easy to resolve.  Also, the exact position of a glider
in a collision can be determined as a function of its diagonal path toward
the collision point, and the time at which it is released, so we need only place
the stable seed on the correct diagonal line for the collision.  It's true that 
these gliders will only go in two of the possible four directions (away from 
the ship), but pairs of gliders arranged for kick-back reactions can overcome 
this deficiency.  At this point, the single problem remaining is how to make 
collisions that require densely packed gliders headed in the same direction.  
Fortunately, these are not needed for glider-gun construction. 

What I would like to see is a set of CAD tools for life.  It would be nice to
be able to specify a layout of logic gates, and have a program turn it into
a pattern of glider guns, then turn this into a collision of gliders, and
ultimately construct a flotilla of spaceships to turn a single glider into
this collision.   By feeding the flotilla with the output of a thin rake,
it should be possible to construct an unbounded linear array of simple 
computing elements.  The result would be a universal machine that could be 
quite small and easily verified.  I would find this to be a more satisfying  
proof of universality than the more general schema of self-replication, which
while certainly correct, requires many details left to the imagination.  

--
Paul Callahan
callahan@cs.jhu.edu

From cellular-automata-request@Think.COM  Fri Jan 11 00:49:56 1991
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Date: Thu, 10 Jan 91 22:49:42 MST
From: cgl%t13@LANL.GOV (Chris Langton)
Message-Id: <9101110549.AA16886@t13.lanl.gov.>
To: ca@Think.COM
Subject: Constructive proof of Life's universality...


  The constructive proof of LIFE's universality is in Berelekamp and Conway's
"Winning ways...." book. You (Calahan) must have missed it.

  It starts out showing how to get NOT, AND, and OR gates out of glider
stream collisions, and then shows how to get arbitrarily extensible
memory. 

Look again.....


Cheers!

Chris Langton

Complex Systems Group
MS B213, Theoretical Division		Phone: 505-667-9471
Los Alamos National Laboratory		Email: cgl@t13.lanl.gov
Los Alamos, New Mexico, USA
87545




From cellular-automata-request@Think.COM  Fri Jan 11 02:27:55 1991
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Date: 11 Jan 91 01:19:22 GMT
From: xanthian@zorch.SF-Bay.ORG (Kent Paul Dolan)
Organization: SF-Bay Public-Access Unix
Subject: Re: Request for programming help
Message-Id: <1991Jan11.011922.10566@zorch.SF-Bay.ORG>
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In article <5234@tahoe.unr.edu> miken@wrc.unr.edu (Mike Nicholl) writes:



> I'm trying to write some CA code in Fortran and would appreciate any
> help I can get (advice, references, pseudo-code, or working code). I
> am well aware that Fortran is not appropriate for CA work, but for
> what I need to do it appears to be the best choice at the
> developmental stage. In particular I am having trouble with the
> mechanics of hexagonal lattice structures. Any help would be greatly
> appreciated. Thanks.

> Mike

If your system supports a long expiration cycle, look at
rec.games.programmer, where there have been several recent excellent
articles recently on the care and feeding of hexagonal grids.

(And if anyone saved them, mail me the lot. Guess what I nuked without
backup capability. Sigh.)

Kent, the man from xanth.
<xanthian@Zorch.SF-Bay.ORG> <xanthian@well.sf.ca.us>

From cellular-automata-request@Think.COM  Tue Jan 15 17:31:21 1991
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Date: 15 Jan 91 18:45:33 GMT
From: callahan@server.cs.jhu.edu (Paul Callahan)
Organization: JHU Computer Science Deparment, Baltimore MD
Subject: Re: Questions and comments about Conway's Life (long)
Message-Id: <callahan.663973195@newton.cs.jhu.edu>
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In article <callahan.663546920@newton.cs.jhu.edu> I write:
>The rakes that produce gliders every 24 turns are sufficiently thin to use as 
>components of the constructions.  (I have a rake in xlife format that thins down
>to sixteenths, which I could post/mail if anyone is interested.) The thinness 
>grows exponentially with the size of the construction

[Note: someone asked what a rake is.  For those unfamiliar with that 
terminology, a rake produces gliders (like a glider gun), while moving
forward (like a puffer train).]    

My latter claim seems to have surprised a knowledgable person, so
I am posting my rake. The trick is to use small rakes to produce a certain 
3-glider collision every time a beehive is encountered.  As a result of this, 
a spaceship is formed when the collision point is empty, and a beehive (and a 
block, which is removed) is formed when the collision point contains the 
spaceship created last time.  Thus, we have a rake that can store two states 
(spaceship/no spaceship).  Note that in a stationery construction (a glider gun 
logic circuit, for example), a stationery object, such as a block, is 
sufficient to store a state, while we need a moving object to store a state
in a rake.

Using a period-24 rake, we can form the inverse of a thin rake from the thinly
spaced beehives, by annihilating the beehives with gliders.  Now, by aiming 
another rake into this inverse stream, using a kick-back reaction, we obtain
two streams of gliders, one the inverse, and the other the inverse of the
inverse (i.e. a glider stream as thin as the beehive trail).  Using two more 
rakes at positions carefully chosen for kickback and annihilation collisions, 
we produce a collision of two of the gliders in the spaceship-producing 
collision.  Spurious gliders leaving the collision point can be destroyed with
spaceships.  For the third glider in the spaceship collision, we use a single
period-24 rake.  Here, we are fortunate enough that the spark from the
spaceship produced by the collision actually destroys the unnecessary gliders.
Otherwise, the collision would have been a bit harder to set up.

This is much more fun to watch than to think about (for me, anyway) so I'm 
posting the pattern for those of you who have access to Xlife (available by
ftp from expo.lcs.mit.edu, and probably some other places).  Please excuse the 
size of the file (compressing and uuencoding doesn't help enough to be worth 
it).

--
Paul Callahan
callahan@cs.jhu.edu

---cut here--- 
#O callahan "Paul Callahan,319 NEB,338-7052,235-3804,Goodrich"@galileo.cs.jhu.edu Sat Jan  5 23:13:19 1991
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553 216
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244 50
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604 2
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245 34
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247 33
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248 35
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248 44
267 161
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576 99
875 161
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875 163
876 163
877 162
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880 154
557 60
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861 220
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1165 60
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1072 137
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1192 145
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870 184
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872 183
566 83
567 83
567 84
568 82
568 84
262 184
263 184
264 185
263 183
264 183
1160 224
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856 41
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856 43
552 224
552 225
552 226
1097 126
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234 45
234 46
234 47
235 47
236 46
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829 124
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1193 191
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239 212
768 129
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1049 136
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585 15
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1193 15
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551 17
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552 17
552 18
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1160 18
769 128
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778 143
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417 136
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418 138
1024 137
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1001 136
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722 129
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1000 137
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977 136
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978 137
978 138
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672 129
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953 136
953 139
954 137
954 138
673 128
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674 129
674 130
952 137
952 138
929 136
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930 138
321 136
321 139
322 137
322 138
928 137
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320 137
320 138
624 129
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17 128
17 131
18 129
18 130
625 128
625 131
626 129
626 130
627 135
16 129
16 130

From cellular-automata-request@Think.COM  Wed Jan 16 10:57:03 1991
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From: sct60a.sunyct.edu!sct60a.sunyct.edu!stu@sct60a.sunyct.edu (Stu Card)
Message-Id: <23892 on Wed, 16 Jan 91 10:57:31 EST @sct60a.sunyct.edu>
To: neuron%hplabs.hp.com@nisc.nyser.net
Subject: GA software
Cc: ca%think.com@nisc.nyser.net


Anybody know of any public domain, freeware, shareware or other low-cost
software for genetic algorithms (a la Holland) and/or evolutionary programming
(a la Fogel)?  I will, of course, post a summary of what I receive; please
respond by direct e-mail rather than a posting.

stu

From cellular-automata-request@Think.COM  Wed Jan 16 12:24:00 1991
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To: issnnet-mlist@park.bu.edu, philosop@yorkvm1.bitnet,
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        soft-eng@mwunix.mitre.org, physics@mc.lcs.mit.edu,
        arpanet-bboards@mc.lcs.mit.edu, neuron@hplabs.hpl.hp.com,
        psych@tcsvm.bitnet, vision-list@ADS.COM,
        ir-l%uccvma.bitnet@vm1.nodak.edu, cvnet@vm1.yorku.ca,
        wiley!ai-chi@LLL-LCC.LLNL.GOV
Subject: Neural Net Course and Conference

               NEURAL NETWORKS COURSE AND CONFERENCE AT

                         BOSTON UNIVERSITY


          NEURAL NETWORKS: FROM FOUNDATIONS TO APPLICATIONS

                           May 5-10, 1991

This self-contained 5-day course is sponsored by the Boston University 
Wang Institute, Center for Adaptive Systems, and Graduate Program in 
Cognitive and Neural Systems.  The course provides a systematic 
interdisciplinary introduction to the biology, computation, mathematics, 
and technology of neural networks.  Boston University tutors are 
Stephen Grossberg, Gail Carpenter, Ennio Mingolla, Michael Cohen, Dan 
Bullock, and John Merrill.  Guest tutors are Federico Faggin, 
Robert Hecht-Nielsen, Michael Jordan, Andy Barto, and Alex Waibel.  
Registration fee: $985 (professional) and $275 (student).  Fee includes 
lectures, course notebooks, receptions, meals, coffee services, and 
evening discussion sessions.    

           NEURAL NETWORKS FOR VISION AND IMAGE PROCESSING

                           May 10-12, 1991

This research conference at the Wang Institute will present invited
lectures and contributed posters, herewith solicited, ranging from visual
neurobiology and psychophysics through computational modelling to
technological applications.   Invited speakers include: Stuart Anstis,
Jacob Beck, Gail A. Carpenter, David Casasent, John Daugman, Robert 
Desimone, Stephen Grossberg, Robert Hecht-Nielsen, Ralph Linsker, 
Ennio Mingolla, Alex Pentland, V.S. Ramachandran, Eric Schwartz, 
George Sperling, James Todd, and Alex Waxman.  A featured Poster 
Session will be held on May 11.  To present a poster, submit 3 copies 
of an abstract (1 single-spaced page), postmarked by March 1, 1991, 
for refereeing.  Include with the abstract the author's name, address, 
and telephone number.  Mail to VIP Poster Session, Neural Networks 
Conference, Wang Institute of Boston University, 72 Tyng Road, Tyngsboro, 
MA 01879.  Authors will be informed of abstract acceptance by March 31, 
1991.  Registration fee: $95 (professionals) and $75 (student).  Fee 
includes lectures and poster session, abstract book, reception, meals, 
and coffee services.   

TO REGISTER: For one or both events by phone, call (508) 649-9731 with VISA
or MasterCard between 9 a.m. - 5 p.m. (EST).  For a meeting brochure, call 
as above or write: Neural Networks, Wang Institute of Boston University, 
72 Tyng Road, Tyngsboro, MA 01879.  


From cellular-automata-request@Think.COM  Wed Jan 16 15:02:51 1991
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                  PRELIMINARY CALL FOR PARTICIPATION
                  ==================================

                                AISB91
                         University of Leeds
                           16-19 April 1991

Interested to know what is happening at the forefront  of  current  AI
research?

Tired of going to AI conferences where you hear nothing but talk about
applications?

Bored at big AI conferences where there are so many parallel  sessions
that you don't know where to go?

Saturated with small workshops that focus only on one narrow topic  in
AI?


     ==> the 1991 AISB conference may be just the thing for you !

AISB91 is organized  by  the  Society  for  the  Study  of  Artificial
Intelligence  and  Simulation  of Behaviour. It is not only the oldest
regular  conference  in  Europe  on  AI  -  which  spawned  the   ECAI
conferences  in  1982  -  but  it  is  also  the conference that has a
tradition of focusing on research as opposed to applications.

The 1991 edition of the conference is no different  in  this  respect.
The conference has a single session and covers the full spectrum of AI
work,  from  robotics  to  knowledge  systems.  It  is  designed   for
researchers active in AI who want to follow the complete field. Papers
were  selected  that  are   representative   for   ongoing   research,
particularly  for  research  topics  that promise new exciting avenues
into a deeper understanding of intelligence.

There will be a tutorial programme on Tuesday 16  April,  followed  by
the technical programme from Wednesday 17 to Friday 19 April.

The conference will be held at Bodington Hall, University of Leeds,  a
large  student  residence  and  conference centre. Bodington Hall is 4
miles from the centre of Leeds and set in 14 acres of private grounds.
Leeds/Bradford  airport  is  6  miles away, with frequent flights from
London  Heathrow,  Amsterdam  and  Paris.  Leeds  itself   is   easily
accessible  by  rail (2 and a half hours from London) and the motorway
network.  The Yorkshire Dales National  Park  is  close  by,  and  the
historic city of York is only 30 minutes away by rail.

TECHNICAL PROGRAMME  Wednesday 17 - Friday 19 April 1991
========================================================
The technical programme sessions are organized around  problem  areas,
not  around approaches. This means sessions show how different schools
of AI - knowledge-based approaches, logic based approaches, and neural
networks - address the fundamental problems of AI.

The technical programme lasts 2 and  a  half  days.  Each  day  has  a
morning  session  focusing  on  a particular area of AI. The first day
this area is distributed AI, the second day new  modes  of  reasoning,
and  the third day theorem proving and machine learning. The afternoon
is devoted to research topics which are at the  forefront  of  current
research.  On the first afternoon this topic is emergent functionality
and autonomous agents.  It  presents  the  new  stream  of  ideas  for
building  autonomous  agents  featuring  concepts  like  situatedness,
physical symbol grounding, reactive systems,  and  emergence.  On  the
second  day  the  topic is knowledge level expert systems research. It
reflects the paradigm shift currently experienced in  knowledge  based
systems  away  from  the symbol level and towards the knowledge level,
both for design and knowledge acquisition. Each session  has  first  a
series  of accepted papers, then two papers which treat the main theme
from a principled point of view, and finally a panel.

In addition the conference features three exciting  invited  speakers:
Andy  Clark  who talks about the philosophical foundations of AI, Rolf
Pfeifer who reflects on AI and emotion, and Tony Cohn who looks at the
formal  modeling  of  common  sense.  The  conference is closed by the
Programme  Chairman,  Luc  Steels,  who  speculates  on  the  role  of
consciousness in Artificial Intelligence.

Here is a more detailed description of the various  sessions  and  the
papers contained in them:

Distributed Intelligent Agents
==============================

Research in distributed AI  is  concerned  with  the  problem  of  how
multiple agents and societies of agents can be organized to co-operate
and collectively solve a problem. The first paper by Chakravarty (MIT)
focuses  on  the problem of evolving agents in the context of Minsky's
society of mind theory. It addresses the question how new  agents  can
be  formed  by  transforming  existing ones and illustrates the theory
with an example from game playing. Smieja (GMD,  Germany)  focuses  on
the  problem of organizing networks of agents which consist internally
of neural networks. Smieja builds upon the seminal work  of  Selfridge
in  the  late  fifties  on the Pandemonium system. Bond (University of
California) addresses the problem of regulating  co-operation  between
agents.  He  seeks  inspiration  in sociological theory and proposes a
framework based on negotiation. Finally Mamede and Martins  (Technical
University   of   Lisbon)  address  the  problem  of  resource-bounded
reasoning within the context of logical inference.

Situatedness and emergence in autonomous agents
===============================================

Research on robots and autonomous agents used to be  focused  strongly
on  low  level mechanisms. As such there were few connections with the
core problems of AI. Recently, there has  been  a  shift  of  emphasis
towards the construction of complete agents. This has lead to a review
of some traditional concepts, such as the  hierarchical  decomposition
of  an agent into a perception module, a decision module and an action
module and it has returned robotics research to the front  of  the  AI
stage.  This session testifies to the renewed interest in the area.

It starts with a paper by Bersini (Free University of Brussels)  which
is strongly within the new perspective of emphasizing situatedness and
non-symbolic relations between perception and action. It discusses the
trade-offs  between  reactive  systems and goal-oriented systems. Seel
(STC Technology, Harlow, UK) provides some of the  formal  foundations
for  understanding  and building reactive systems. Jackson and Sharkey
(University of Exeter) address the problem of  symbol  grounding:  how
signals can be related to concepts. They use a connectionist mechanism
to relate spatial descriptions with  results  from  perception.  Cliff
(University  of  Sussex)  discusses  an  experiment  in  computational
neuroethology.

The next paper is from the Edinburgh Really Useful Robot project which
has  built up a strong tradition in building autonomous mobile robots.
The paper will be  given  by  Hallam  (University  of  Edinburgh)  and
discusses an experiment in real-time control using toy cars. The final
paper is by Kaelbling (Teleos Research,  Palo  Alto,  California)  who
elaborates  her  proposals  for  principled  programming of autonomous
agents based on logical specifications.

The panel which ends the session tries to  put  the  current  work  on
autonomous  agents  into  the  broader  perspective  of  AI. The panel
includes  Smithers  (University  of  Edinburgh),   Kaelbling,   Connah
(Philips Research, UK), and Agre (University of Sussex).

Following this session, on Wednesday evening,  the  conference  dinner
will  be  held  at  the  National  Museum  of  Photography,  film  and
Television at Bradford. The evening will include a special showing  in
the IMAX auditorium, which has the largest cinema screen in Britain.

New modes of reasoning
======================

Reasoning remains one of the core topics of AI. This session  explores
some  of  the  current  work to find new forms of reasoning. The first
paper by Hendler and Dickens (University of  Maryland)  looks  at  the
integration  of  neural  networks  and symbolic AI in the context of a
concrete example involving an underwater robot.  Euzenat  and  Maesano
(CEDIAG/Bull, Louveciennes, France) address the problem of forgetting.
Pfahringer (University  of  Vienna)  builds  further  on  research  in
constraint   propagation  in  qualitative  modelling.  He  proposes  a
mechanism to improve efficiency through domain variables. Ghassem-Sani
and  Steel  (University  of  Essex)  extend the arsenal of methods for
non-recursive  planning  by  introducing   a   method   derived   from
mathematical induction.

The knowledge level perspective
===============================

Knowledge systems (also known as  expert  systems  or  knowledge-based
systems)  continue  to  be the most successful area of AI application.
The conference does not focus  on  applications  but  on  foundational
principles  for building knowledge systems. Recently there has been an
important shift of emphasis from symbol  level  considerations  (which
focus  on the formalism in which a system is implemented) to knowledge
level considerations. The session highlights this shift in emphasis.

The first paper by Pierret-Golbreich  and  Delouis  (Universite  Paris
Sud) is related to work on the generic task architectures. It proposes
a framework including support tools for  performing  analysis  of  the
task  structure  of  the  knowledge  system.  Reichgelt  and  Shadbolt
(University of Nottingham) apply the knowledge  level  perspective  to
the problem of knowledge acquisition. Wetter and Schmidt (IBM Germany)
focus on the formalization of the KADS interpretation models which  is
one  of the major frameworks for doing knowledge level design. Finally
Lackinger and Haselbock (University of Vienna) focus on domain  models
in  knowledge  systems, particularly qualitative models for simulation
and control of dynamic systems.

Then there are two papers which directly address foundational  issues.
The  first  one  by  Van de Velde (VUB AI Lab, Brussels) clarifies the
(difficult) concepts involved in knowledge level discussions of expert
systems,   particularly   the  principle  of  rationality.  Schreiber,
Akkermans and Wielinga (University of  Amsterdam)  critically  examine
the suitability of the knowledge level for expert system design.

The  panel  involves  Leitch  (Heriot  Watt  University,   Edinburgh),
Wielinga,  Van  de  Velde,  Sticklen  (Michigan State University), and
Pfeifer (University of Zurich).

Theorem proving and Machine learning
===============     ================

The final set of papers focuses on recent work in theorem proving  and
in  machine  learning.  The  first  paper by Giunchiglia (IRST Trento,
Italy) and Walsh (University of Edinburgh) discusses  how  abstraction
can  be  used  in  theorem proving and presents solid evidence to show
that it  is  useful.  Steel  (University  of  Essex)  proposes  a  new
inference scheme for modal logic.

Then there are two papers which  represent  current  work  on  machine
learning.  The  first  one  by  Churchill  and  Young  (University  of
Cambridge)  reports  on  an  experiment  using  SOAR  concerned   with
modelling  representations  of  device  knowledge. The second paper by
Elliott and Scott (University of Essex)  compares  instance-based  and
generalization-based learning procedures.

TUTORIAL PROGRAMME - Tuesday 16 April 1991
==========================================

Six full-day tutorials will be offered on 16 April (subject to sufficient
registrations for each.)

Tutorial 1  Knowledge Base Coherence Checking
----------
Professor Jean-Pierre LAURENT
University of Savoie
FRANCE

Like conventional software, AI Systems  also  need  validation  tools.
Some  of  these  tools  must  be  specific,  especially for validating
Knowledge-Based Systems, and in particular for checking the  coherence
of  a  Knowledge  Base  (KB).  In the introduction to this tutorial we
will  clarify  the  distinctions  to  be  made   between   Validation,
Verification, Static Analysis and Testing.

We will present methods  which  try  to  check  exhaustively  for  the
coherence  of  a  knowledge  Base.  Then  we  will present a pragmatic
approach in which, instead of trying to assert the global coherence of
a  KB,  it  is  proposed  to  check  heuristically whether it contains
incoherences. This  approach  is  illustrated  by  the  SACCO  System,
dealing  with  KBs  which contain classes and objects, and furthermore
rules with variables.

Tutorial 2  Advanced Constraint Techniques
----------
Dr. Hans Werner Guesgen and Dr. Joachim Hertzberg
German National Centre for Computer Science (GMD)
Sankt Augustin,
GERMANY

This tutorial will present a coherent  overview  of  the  more  recent
concepts  and  approaches  to  constraint  reasoning.  It presents the
concept of dynamic constraints  as  a  formalism  subsuming  classical
constraint   satisfaction,  constraint  manipulation  and  relaxation,
bearing a relationship to reflective systems; moreover,  the  tutorial
presents   approaches   to   parallel  implementations  of  constraint
satisfaction in general and dynamic constraints in particular.

Tutorial 3  Functional Representation and Modeling
----------
Prof. Jon Sticklen and Dr. Dean Allemang*
Michigan State University
USA

* Universitaet Zurich, SWITZERLAND

A growing body of AI research centres on using the known functions  of
a device as indices to causal understanding of how the device "works".
The results of functional representation and modeling  have  typically
used  this  organization  of causal understanding to produce tractable
solutions to inherently complex modelling problems.

In this tutorial, the fundamentals of  functional  representation  and
reasoning  will  be explained. Liberal use of examples throughout will
illustrate the representational  concepts  underlying  the  functional
approach.  Contacts  with other model based reasoning (MBR) techniques
will be made whenever appropriate.

Sufficient background will be covered to make this suitable  for  both
those  unacquainted  with  the  MBR  field,  and  for more experienced
individuals who  may  be  working  now  in  MBR  research.  A  general
familiarity with AI is assumed.

Participants should send in with their registration  materials  a  one
page  description  of  a  modeling  problem  which  they face in their
domain.

Tutorial 4   Intelligent Pattern Recognition and Applications
----------

Prof. Patrick  Wang  M.I.T.  Artificial  Intelligence  Laboratory  and
Northeastern University, Boston USA

The core of pattern recognition, including "learning  techniques"  and
"inference"  plays  an important and central role in AI.  On the other
hand, the methods in AI such  as  knowledge  representation,  semantic
networks,  and  heuristic  searching algorithms can also be applied to
improve the pattern representation and  matching  techniques  in  many
pattern recognition problems - leading to "smart" pattern recognition.
Moreover, the recognition  and  understanding  of  sensory  data  like
speech  or  images,  which  are major concerns in pattern recognition,
have always been considered as important subfields of AI.

This  tutorial  includes  overviews   of   pattern   recognition   and
articifical  intelligence;  including recent developments at MIT.  The
focus of the tutorial will be on the  overlap  and  interplay  between
these fields.

Tutorial 5 SILICON SOULS - Philosophical foundations of computing and AI
----------
Prof. Aaron Sloman
University of Birmingham

This will not be a technical tutorial. Rather the tutor will introduce
a   collection   of   philosophical  questions  about  the  nature  of
computation, the  aims  of  AI,  connectionist  and  non-connectionist
approaches  to  AI, the relevance of computation to the study of mind,
varieties of mechanism, consciousness, and the nature of emotions  and
other  affective  states.  Considerable  time  will  be  provided  for
discussion by participants.

Prof. Sloman has provided a list of pertinent questions, these will be
sent to participants upon registration.

Tutorial 6 Knowledge Acquisition
--------
Dr. Nigel Shadbolt
Nottingham University

Practical methods for acquiring knowledge from  experts.  The  methods
described  have  been  shown  to  be  effective through the pioneering
research at Nottingham which compared common and less  common  methods
for eliciting knowledge from experts.

This tutorial is an  updated  version  of  the  knowledge  acquisition
tutorial given at AISB'89 which was well-attended and enthusiastically
received.

========================================================================

For further information on the tutorials, mail tutorials@hplb.hpl.hp.com or
tutorials@hplb.lb.hp.co.uk or tutorials%hplb.uucp@ukc.ac.uk

For a conference programme and registration form, or general information
about the conference, mail aisb91@ai.leeds.ac.uk or write to:

Barbara Smith
AISB91 Local Organizer
School of Computer Studies
University of Leeds
Leeds LS2 9JT
U.K.

























9

9




From cellular-automata-request@Think.COM  Thu Jan 17 09:50:35 1991
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Date: 17 Jan 91 11:27:57 GMT
From: angelo@gem.stack.urc.tue.nl (Angelo Wentzler)
Organization: Stack, Eindhoven University of Technology, The Netherlands
Subject: Re: Questions and comments about Conway's Life (long)
Message-Id: <133@gem.stack.urc.tue.nl>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM

All very fine and very interesting, mr.Callahan, but could you please explain
to me what the following cell-groups are:
Spaceship,spark,glider,rake,block.

I presume a block is like this:   ....
                                  .**.
                                  .**.
                                  ....

I know a glider of the following shape:  .....
                                         .***.
                                         ...*.
                                         ..*..
                                         .....

But yours seems to be a bit larger.

Perhaps a spark is what I call a blinky:   ......
                                           .**...
                                           .*....
                                           ....*.
                                           ...**.
                                           ......
Oh yes, what is a beehive? And a glider gun?
If you let me know, perhaps a nice discussion could start...

From cellular-automata-request@Think.COM  Thu Jan 17 13:15:01 1991
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Date: 17 Jan 91 11:27:57 GMT
From: angelo@gem.stack.urc.tue.nl (Angelo Wentzler)
Organization: Stack, Eindhoven University of Technology, The Netherlands
Subject: Re: Questions and comments about Conway's Life (long)
Message-Id: <133@gem.stack.urc.tue.nl>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM

All very fine and very interesting, mr.Callahan, but could you please explain
to me what the following cell-groups are:
Spaceship,spark,glider,rake,block.

I presume a block is like this:   ....
                                  .**.
                                  .**.
                                  ....

I know a glider of the following shape:  .....
                                         .***.
                                         ...*.
                                         ..*..
                                         .....

But yours seems to be a bit larger.

Perhaps a spark is what I call a blinky:   ......
                                           .**...
                                           .*....
                                           ....*.
                                           ...**.
                                           ......
Oh yes, what is a beehive? And a glider gun?
If you let me know, perhaps a nice discussion could start...

From cellular-automata-request@Think.COM  Thu Jan 17 13:51:15 1991
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Date: 17 Jan 91 17:59:24 GMT
From: callahan@server.cs.jhu.edu (Paul Callahan)
Organization: JHU Computer Science Deparment, Baltimore MD
Subject: Re: Questions and comments about Conway's Life (long)
Message-Id: <callahan.664135291@newton.cs.jhu.edu>
Newsgroups: comp.theory.cell-automata
References: <133@gem.stack.urc.tue.nl>
Sender: ca-request@Think.COM
To: ca@Think.COM

In article <133@gem.stack.urc.tue.nl> angelo@gem.stack.urc.tue.nl (Angelo Wentzler) writes:
>All very fine and very interesting, mr.Callahan, but could you please explain
>to me what the following cell-groups are:
>Spaceship,spark,glider,rake,block.

I guess my first response has to be something like: if you don't know, then you
probably won't be able to help me.  I know that sounds horrible; it's just that
I was writing a long article with limited time, and I didn't feel like spending
too much timing giving my own definitions of "well known" patterns.  All the 
patterns I mentioned are defined in either _Winning Ways for All Your 
Mathematical Plays_ by Berlekamp, Conway, and Guy or _The Recursive Universe_ 
by William Poundstone.  I've seen some variations on names in the files provided
with Xlife.

To be brief: gliders and blocks are as you supposed (I don't know why you say
that my notion of gliders is a larger pattern.  Perhaps you could be more 
specific.)  For the other constructions:

Spaceships (called "fish" in Xlife files) come in three sizes: small, medium,
and large.  They are as follows ("sparks" shown capitalized): 

X..x.
....x   (small)
x...x
.xxxx

..X...
X...x.
.....x   (medium)
x....x
.xxxxx

..XX...
X....x.
......x   (large)
x.....x
.xxxxxx


Spaceships move along x or y axes.  Sparks have the property that they are 
produced by a spaceship, but can be removed without destroying it.  They are
useful for creating effects in which a spaceship passes by a pattern and affects
it while escaping unharmed.

A rake is an object that moves in the same way as a spaceship, but leaves a
trail of gliders in its wake.  These trails can be collided to produce stable
objects, and other interesting things (such as a variety of "puffer train" 
effects).  

My goal was to determine if a set of rakes producing gliders at very wide
intervals could be used to directly construct a Turing Machine within the
Life universe.  I know it _can_ be done, but I was interesting in knowing if
an explicit construction had been given.  My idea was to duplicate the
finite head logic in every tape cell, though I now feel that that is ambitious
even for the smallest known Universal Turing Machine (its state set and 
alphabet both number in the single digits--I don't have the exact numbers
at my finger tips).  

I have another idea for an even simpler universal model of computation, which 
I will continue in the following posting. 

--
Paul Callahan
callahan@cs.jhu.edu

From cellular-automata-request@Think.COM  Thu Jan 17 16:51:00 1991
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Date: 17 Jan 91 18:18:19 GMT
From: callahan@server.cs.jhu.edu (Paul Callahan)
Subject: What is the simplest universal machine to implement in Conway's Life?
Message-Id: <callahan.664145444@newton.cs.jhu.edu>
Newsgroups: comp.theory.cell-automata,comp.theory
Sender: ca-request@Think.COM
To: ca@Think.COM

From what I've gathered, no explicit construction has yet been given for a 
universal machine within Conway's Life (*please* correct me if I'm wrong), even 
though it is more or less clear to everyone that all the pieces exist to do so.
A question that I've played with for a while, but only really began thinking 
about recently is whether there exists a computational model, sufficiently 
simple to construct explicitly within Life, whose universality can be proven 
independent of the assumption that Life is universal.

Clearly, any such machine will need to have some kind of infinite component, 
but fortunately, it is possible to use a finite construction to build up this
component (e.g. memory or tape cells) at a pace that exceeds the pace
of computation (the result being effectively infinite storage). I've gone into
this in some detail in a previous posting to comp.theory.cell-automata, so I
won't discuss it here.

The architecture chosen in the references I've seen (e.g. _Winning Ways_ by
Berlekamp, Conway, and Guy) resembles that of a modern electronic
computer (i.e. Von Neumann architecture), and I believe that this
may not be the simplest universal computer to construct within Life.

My suggestion in a previous posting was that a Turing Machine would be
easier to implement.  However, the construction of an actual moving head
is very difficult.  Instead, my plan was to duplicate the head logic
in every tape cell, effectively constructing a 1-D cell-automaton within
Life.  Even for the smallest known universal TM, the head logic is still fairly
hefty to build a "breeder-like" constructor for it, so it now occurs to me
that a kind of hybrid automaton might be preferable. 

The hybrid I have in mind is a semi-infinite 1-D cell-automaton with the
same transition function on all cells except the leftmost one.  Ideally,
the uniform component would have a very small set of states and a simple
transition function, while the leftmost cell would be sufficiently complex
to simulate the finite control of a universal TM.  The transition function
of the leftmost cell would depend on its state and the output of its right
neighbor, while the state of an internal cell would depend on its own state
and the state of its two neighbors.  We assume that the neighbor of the
leftmost cell will not use the actual state of the latter, but rather the 
result of a function mapping that state to the states of internal nodes.

It is not hard to see that such an automaton can be universal without requiring
the assumption that the infinite component itself be universal.  For example, 
each cell could contain a flag asserting whether or not it is the current head 
position, and read/write/move-head requests could propagate from the leftmost 
cell, which we could make as complex as we needed it to be.

I'm wondering how simple we can make the transition function in the infinite
component.  Ideally, we would like to have no more than two states per cell
in this part, and it would be desirable to make the function dependent only 
upon the states of the neighbors of a cell, and not upon the state of the cell 
itself (i.e., the least necessary to allow bidirectional communication.)  
I have a specific candidate in mind that strikes me as difficult to prove 
universal, but doesn't seem likely to fit into any other well known
category either. 

Suppose we let the infinite component consist of cells with states in {0,1}, 
and let the transition function of each cell be the parity function of its 
two neighbors' states (in other words, exclusive-or, or sum mod 2) .  Given 
such an automaton alone, we may construct a parity expression defining the 
value of any cell at time t in terms of other cells at time 0.  The size of 
this expression is O(t) (proof left as an exercise), so the automaton does not 
seem powerful enough to be universal.  However, the introduction of a more 
complex finite automaton for the leftmost cell makes the situation much more 
difficult.  In this case, we can write the value of a cell as a parity 
expression in terms of other cells at time 0 *and* the outputs of the leftmost 
cell at times 0,1,...,t.  (Let the output of the leftmost cell be a function 
of its state to {0,1}).  These outputs are themselves functions of cell values,
so it seems that some non-trivial computation may be possible.  

If we think of the leftmost cell as a finite control, then the contents of
an infinite memory (i.e. the parity automaton) are cycling by this cell in
some well-defined manner.  This finite control can read and write to this 
memory, but it is not entirely clear (to me) how it can exploit it to simulate 
a Turing Machine.  The memory does not seem to restrict access to information
the way a stack does, but the information travels past the head in such an
unusual way that it seems a good deal of cleverness would be required to use 
the infinite component as a read/write tape.  I haven't thought it through
completely, I have to admit, but I think it would be very interesting if it
could be shown to be universal or proven not to accept some restricted class of
languages.  If anyone has any ideas, or knows of a reference that treats 
something very close to this question, I'd be interested.

By the way, the fact that the head cannot control the way in which data "moves"
past it is not itself a reason to reject the possibility of universality.  
Another universal machine I was considering with aims to build a simple 
computer in Life would use a uni-directional tape-loop that added a blank
cell every time the tape completed a cycle.  In this case, the head could
simulate backing up by marking its current spot and waiting for the tape
to come around again (As a friend of mine pointed out, it won't "know" 
it has found its new location until it has passed it, so it will have to
move all the data on the tape forward to simulate backing up; this is
easy to accomplish with a suitable finite control).

Please excuse the somewhat rambling nature of this posting.  My specific
question is whether the above automaton (which I can formalize if necessary) 
is universal, while my more general question is whether or not some very simple
universal machine exists that might be constructed easily within Life.  I'm 
inclined to think that a hybrid cell-automaton along the lines I propose (with
leftmost cell layed out "by hand" and internal cells constructed by a type of
"breeder") would be the best bet, but I am open to any other ideas.

--
Paul Callahan
callahan@cs.jhu.edu

From cellular-automata-request@Think.COM  Thu Jan 17 18:18:39 1991
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Date: Thu, 17 Jan 1991 18:13-0500
From: Allan C. Wechsler <ACW@YUKON.SCRC.Symbolics.COM>
Subject: What is the simplest universal machine to implement in Conway's Life?
To: callahan@server.cs.jhu.edu, ca@Think.COM, RWG@YUKON.SCRC.Symbolics.COM
In-Reply-To: <callahan.664145444@newton.cs.jhu.edu>
Message-Id: <19910117231342.5.ACW@WHIMBREL.SCRC.Symbolics.COM>

I have a few ideas, most of them from Gosper, whom I've copied.

A three- or four-counter machine would be easier to implement than a TM,
and is just as universal.  Use four blocks as the counters.  Known
glider reactions can increment them, decrement them, and test them for
zeroness.

If you must implement a TM, how about the following architecture?  The
tape is a semi-infinite stack of zones, each of which either contains or
lacks a block.  There is no per-cell logic.  To read a cell, you shoot a
pair of gliders through it, along a path perpendicular to the tape.  One
of the gliders is aimed to miss the block even if it is present; the
other is aimed at the putative block in such a way that it is
annihilated without damaging the block if the block is present, and just
passes through the cell if the block is absent.  Two gliders go in: if
the block is present, one glider comes out, otherwise two.

The CPU is at the end of the tape.  To read a cell, it shoots a salvo of
two gliders parallel to the tape.  These gliders travel along the tape
until they encounter the read-write head, which consists of a set of
mirrors arranged symmetrically on both sides of the tape.  (A
properly-positioned block can act as a mirror.)  The read salvo is
deflected into the tape by the head.  On the other side, the return
mirrors bounce the salvo (either one or two gliders) back toward the
CPU.  The glider that never interacts with the tape is just a timing
pulse, allowing the CPU to wait patiently while the read salvo goes out
and returns.

To write a zero, a zap glider and a timing glider go up one side of the
tape.  The head bounces them in, and the zap glider destroys the block.
The timing glider comes back to the CPU to say that the job has been
done.

To write a one, gliders have to be fired up both sides of the tape.  I
believe there are head-on collisions that can create blocks.  If this is
true, the write-a-one salvo only needs three gliders: one from each side
of the tape to build the block and one timing glider.

I count a minimum of seven mirrors in the head.

To move the head, we need to send a tedious series of extend or retract
salvos at each mirror.  These (known) salvos push a block farther away
or draw it back, but only by a few cells.  Assuming that each tape zone
is on the order of a hundred life cells long, we might have to send
around a hundred phased salvos at each mirror.  At the end of the motion
sequence, we send one timing glider up to the head to verify that the
operation is complete.

The hardest problem is arranging the mirrors of the head so they can
fire past each other on slightly different paths without destroying each
other.  This could be solved by using a smaller number of mirrors, and
incorporating auxiliary gliders in our salvos that perturb the course of
the function gliders after they have been reflected.  The timing mirrors
can be far out of the way, but the five read/write mirrors are all
almost in line and may need this treatment.


From cellular-automata-request@Think.COM  Fri Jan 18 09:24:57 1991
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Date: 17 Jan 91 18:18:19 GMT
From: callahan@server.cs.jhu.edu (Paul Callahan)
Subject: What is the simplest universal machine to implement in Conway's Life?
Message-Id: <callahan.664145444@newton.cs.jhu.edu>
Newsgroups: comp.theory.cell-automata,comp.theory
Sender: ca-request@Think.COM
To: ca@Think.COM

From what I've gathered, no explicit construction has yet been given for a 
universal machine within Conway's Life (*please* correct me if I'm wrong), even 
though it is more or less clear to everyone that all the pieces exist to do so.
A question that I've played with for a while, but only really began thinking 
about recently is whether there exists a computational model, sufficiently 
simple to construct explicitly within Life, whose universality can be proven 
independent of the assumption that Life is universal.

Clearly, any such machine will need to have some kind of infinite component, 
but fortunately, it is possible to use a finite construction to build up this
component (e.g. memory or tape cells) at a pace that exceeds the pace
of computation (the result being effectively infinite storage). I've gone into
this in some detail in a previous posting to comp.theory.cell-automata, so I
won't discuss it here.

The architecture chosen in the references I've seen (e.g. _Winning Ways_ by
Berlekamp, Conway, and Guy) resembles that of a modern electronic
computer (i.e. Von Neumann architecture), and I believe that this
may not be the simplest universal computer to construct within Life.

My suggestion in a previous posting was that a Turing Machine would be
easier to implement.  However, the construction of an actual moving head
is very difficult.  Instead, my plan was to duplicate the head logic
in every tape cell, effectively constructing a 1-D cell-automaton within
Life.  Even for the smallest known universal TM, the head logic is still fairly
hefty to build a "breeder-like" constructor for it, so it now occurs to me
that a kind of hybrid automaton might be preferable. 

The hybrid I have in mind is a semi-infinite 1-D cell-automaton with the
same transition function on all cells except the leftmost one.  Ideally,
the uniform component would have a very small set of states and a simple
transition function, while the leftmost cell would be sufficiently complex
to simulate the finite control of a universal TM.  The transition function
of the leftmost cell would depend on its state and the output of its right
neighbor, while the state of an internal cell would depend on its own state
and the state of its two neighbors.  We assume that the neighbor of the
leftmost cell will not use the actual state of the latter, but rather the 
result of a function mapping that state to the states of internal nodes.

It is not hard to see that such an automaton can be universal without requiring
the assumption that the infinite component itself be universal.  For example, 
each cell could contain a flag asserting whether or not it is the current head 
position, and read/write/move-head requests could propagate from the leftmost 
cell, which we could make as complex as we needed it to be.

I'm wondering how simple we can make the transition function in the infinite
component.  Ideally, we would like to have no more than two states per cell
in this part, and it would be desirable to make the function dependent only 
upon the states of the neighbors of a cell, and not upon the state of the cell 
itself (i.e., the least necessary to allow bidirectional communication.)  
I have a specific candidate in mind that strikes me as difficult to prove 
universal, but doesn't seem likely to fit into any other well known
category either. 

Suppose we let the infinite component consist of cells with states in {0,1}, 
and let the transition function of each cell be the parity function of its 
two neighbors' states (in other words, exclusive-or, or sum mod 2) .  Given 
such an automaton alone, we may construct a parity expression defining the 
value of any cell at time t in terms of other cells at time 0.  The size of 
this expression is O(t) (proof left as an exercise), so the automaton does not 
seem powerful enough to be universal.  However, the introduction of a more 
complex finite automaton for the leftmost cell makes the situation much more 
difficult.  In this case, we can write the value of a cell as a parity 
expression in terms of other cells at time 0 *and* the outputs of the leftmost 
cell at times 0,1,...,t.  (Let the output of the leftmost cell be a function 
of its state to {0,1}).  These outputs are themselves functions of cell values,
so it seems that some non-trivial computation may be possible.  

If we think of the leftmost cell as a finite control, then the contents of
an infinite memory (i.e. the parity automaton) are cycling by this cell in
some well-defined manner.  This finite control can read and write to this 
memory, but it is not entirely clear (to me) how it can exploit it to simulate 
a Turing Machine.  The memory does not seem to restrict access to information
the way a stack does, but the information travels past the head in such an
unusual way that it seems a good deal of cleverness would be required to use 
the infinite component as a read/write tape.  I haven't thought it through
completely, I have to admit, but I think it would be very interesting if it
could be shown to be universal or proven not to accept some restricted class of
languages.  If anyone has any ideas, or knows of a reference that treats 
something very close to this question, I'd be interested.

By the way, the fact that the head cannot control the way in which data "moves"
past it is not itself a reason to reject the possibility of universality.  
Another universal machine I was considering with aims to build a simple 
computer in Life would use a uni-directional tape-loop that added a blank
cell every time the tape completed a cycle.  In this case, the head could
simulate backing up by marking its current spot and waiting for the tape
to come around again (As a friend of mine pointed out, it won't "know" 
it has found its new location until it has passed it, so it will have to
move all the data on the tape forward to simulate backing up; this is
easy to accomplish with a suitable finite control).

Please excuse the somewhat rambling nature of this posting.  My specific
question is whether the above automaton (which I can formalize if necessary) 
is universal, while my more general question is whether or not some very simple
universal machine exists that might be constructed easily within Life.  I'm 
inclined to think that a hybrid cell-automaton along the lines I propose (with
leftmost cell layed out "by hand" and internal cells constructed by a type of
"breeder") would be the best bet, but I am open to any other ideas.

--
Paul Callahan
callahan@cs.jhu.edu

From cellular-automata-request@Think.COM  Mon Jan 21 16:32:16 1991
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Date: 21 Jan 91 19:07:59 GMT
From: kawl@quads.uchicago.edu (david john kawliche)
Organization: University of Chicago
Subject: Life Wars
Message-Id: <1991Jan21.190759.3684@midway.uchicago.edu>
Newsgroups: comp.theory.cell-automata
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	I have recently written a program (in LSC 4.0, for the mac)
that allows two 'teams' of cellular automata to be grown in the same
medium.  The interactions between cells of the same type can be set
and so can the interactions between cells of differing types.  I have 
gotten some very interseting results in the first few passes at this sort
of simulation and believe that the possiblity for warring, symbiotic, 
segragationalist and other general behaviors are possible.  I am interested
in knowing if anyone has done this before, and if there is interest in 
such a program.

From cellular-automata-request@Think.COM  Tue Jan 22 00:32:44 1991
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Date: 22 Jan 91 00:20:10 GMT
From: callahan@server.cs.jhu.edu (Paul Callahan)
Subject: Extendable "delay loop" memory for universal machine in Life
Message-Id: <callahan.664517398@newton.cs.jhu.edu>
Newsgroups: comp.theory,comp.theory.cell-automata
Sender: ca-request@Think.COM
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I have not yet constructed an explicit universal machine in Life.  However,
I have constructed a potentially infinite memory component that I believe
will make it easier to do so.  Before explaining this pattern (included
with the posting) I feel obligated to clear up some misleading statements
I made in a previous posting.

It has been a long time since I read _The Recursive Universe_ (Poundstone), 
and at the time I was under the false impression that its proof of life 
universality relied on the ability to construct boolean logic gates which 
could then be layed out in arbitrarily large networks by a universal 
constructor.  I seem to have neglected the very elegant proof of universality 
(by Conway himself, and treated in detail in _The Recursive Universe_) that is 
implied by the existence of sliding block memories.  

These memories make it possible to store an arbitrarily large integer 
accessible by the operations increment, decrement, and test for zero.  It 
is well known that a machine with two such memories (called counters) is 
universal (see, for example, Hopcroft and Ullman _Introduction to Automata 
Theory, Languages, and Computation_), so a universal machine can be constructed
with two sliding block memories and a sufficiently large finite control.
(the input tape could be represented a sequence of gliders going by the
control initially). 

The primary difficulty with a 2-counter machine is that it does not preserve
polynomial time complexity, so it still seems desirable to construct an
unbounded tape-like memory.  After some experimentation, I constructed an
extendable "delay loop" memory.  In such a memory, a character is written to
a stream by the finite control and it arrives back after a number of steps.  The
length of the delay determines the size of the memory.  It is not hard to
see how we may (at a linear time cost) simulate left/right tape moves using 
such a memory.  It is easy to construct large finite delay loops in Life, so 
the primary question is how to construct a delay loop that can be lengthened 
arbitrarily by the finite control.

Before going into the construction, which is rather intricate, it is worthwhile
to point out precisely what is being attempted.  We assume a finite control 
that, at each step, can read an incoming character, write an outgoing character,
and possibly send a signal to lengthen the delay loop.  The character written at
time t is read back at time t+d, where d is a delay parameter that is 
incremented each time a lengthen signal is output by the finite control.
For the actual construction, we assume a two character alphabet.

The method I used to implement the extendable delay loop in Life is a 
pair of spaceship streams going in opposite directions, the forward stream
produced by a stationery gun, and the backward stream produced by a forward-mov-
ing rake flotilla.  In general, we would like these streams to pass without
affecting each other.  However, at a certain distance from the stationery
gun, the presence of spaceships in the forward stream causes holes to be left in
the backward stream (thus forcing data to reverse direction and head back
toward the finite control).  The distance to the point at which the streams 
interact determines the length of the delay loop.

A carefully positioned "eater" (see a standard Life reference) can be used to 
create such an interaction point.  To allow the finite control to adjust the
interaction point, we augment the rake flotilla to produce a sequence of 
eaters in addition to backward moving spaceships.  The leftmost eater will now 
define the length of the delay loop.  To increase the size of the loop, our 
finite control need only send out a spaceship along a path parallel to the 
forward data stream in order to annihilate the leftmost eater.  The distance
to the most distant eater grows very rapidly, so the maximum length of the 
delay loop is effectively unbounded.

The following schematic will (hopefully) be easier to follow than the 
Life pattern itself.  It is still rather involved.  Symbol names
are explained below.  This construction is a simple recirculating loop in
which characters read from the delay loop are written back to it as they
become available.  It is possible to manually force a loop-lengthening signal
within Xlife by erasing a glider, but the pattern is not set up to issue one 
automatically. 

                       /
     gg1       gg2    /     gg3                                            
        \         \  /        \
         x1        x2          \                                             
        / \         \           \                                               
       |   \         \    se<----x3--<--------<-------------<---------\
        \   sg1--->---\-->----->--\----->----->------X                 R
         \             sg2--->-----\-->------>-------e0 e1 e2 e3 ... /
          \                         \                   (ei)            
           \                         | 
            \           -           /                                        
             \         / \         /                                         
              \       /   \       /                                          
               \     /     \     /                                           
                \   /       \   /                                            
                 \ /         \ /                                             
                  -           -                       

Components of Pattern
---------------------
sg1: Spaceship gun producing forward data stream.
gg1: Glider gun to normally inhibit sg1.
ei:  Eater sequence establishing collision points for collision that 
     leaves hole in backward stream when pair of ships arrive in
     forward stream.
sg2: Spaceship gun producing spaceships to lengthen delay loop by 
     destroying leftmost remaining eater in sequence ei.
gg2: Glider gun that normally inhibits sg2.
gg3: Glider gun to test backward data stream by attempting to shoot
     gliders through a hypothetical hole in stream.
R:   Rake flotilla, producing spaceships for backward data stream,
     as well as eater sequence ei.
se:  Eater positioned to destroy spaceships from backward data stream.

(Note: Isolated - and | characters are shuttles placed to reflect
glider stream).

Collision Points
----------------
x1:  Incoming glider hits glider from gg1 and leaves block, also destroying
     next glider from gg1.  (Thus, incoming glider produces pair of
     spaceships, which will eventually result in another incoming glider).
x2:  Properly positioned glider destroys glider from gg2, causing sg2
     to produce a spaceship that lengthens loop by destroying leftmost
     eater. (This collision must be simulated "by hand" in enclosed 
     Xlife file by erasing a glider from gg2).
x3:  Glider attempts to pass through hole in backward data stream.  Thus,
     contents of backward data stream are converted to incoming gliders.
X:   Two consecutive spaceships in forward stream interact with two spaceships
     in backward stream at leftmost eater.  Spaceships are all destroyed, 
     while eater remains unharmed for the next collision (a glider is sent
     Northeast as a useless, but harmless side-effect).

Finally, the rest of this posting will consist of the pattern itself,
in Xlife format.  This pattern produces an initial "1" in the delay loop, formed
by two consecutive spaceships in the forward data stream, and "0" for all other
positions in the delay loop.  It is possible to insert more 1s manually by
destroying *two* consecutive gliders from gg1.  It is important to destroy
them in pairs in order for the eater-interaction to work properly.  It is
possible to turn 1s into 0s manually by destroying *single* gliders travelling 
along the reflector path at the bottom of the construction.  

Explanatory note: A "1" has three primary representations in the course of the 
delay loop: a pair of spaceships in the forward data stream, a gap of two 
spaceships in the backward data stream, and a single glider in the reflector
path.

The following pattern is an Xlife file that has been compressed and uuencoded.

--- cut here ---
begin 644 delayloop.life.Z
M'YV0(YZ`&!.&#9LP:,*X`2$"2I@Z;$`,*7@PH1L6,V+D`.&DB!",,W"TN`&CH
MA@P6,F;4:!$2!@T61]Z\(2,GS1@T(H#8>2/GC9LW:5R,F>-"#9HZ+LJ0J0.B/
MB4\02A2"D!$#1`P<.E3JH+%18XX8"JA:S7$C;%6-.,+*&%LV)=NP,\;6"$M#X
M+MVQ-L+BL(HCKXR]5]L"QI%61E<<;0\7CAL8+M_"=:_ZC8SX[M7"-?C.")OYS
MZEP9G?N&M:%Y-%^_-TK+2.TY+&O18F/<^'SVAM^ULOTRMNU8-F2K-]I&OI%6"
M]MH9-,#*KHI<.5<0S17$J`$#>G+IU*'/R(&].G(8V)F'Q'Y\_/3RW&/8J#M#E
MI?3UVO.J9S^CK/J-[8O;P+]=.DGMQ=T@7GH"6@>>>MZU]UZ"-"P(H(/MI6>#F
M>`VJ)]Y<%L;WGGCV3?B@>N55:$-Y&(ZH78?EZ1=7>R*NZ)YZ+G;H8F$V["6#^
M8:-E=B-W,MB@XPS@]9A:2D'6.!5HH]G88Y)'TKC1C7[MUZ1KU=W85H%6NJ:CR
M#`VNMN5G/A[999@W@DE:ED**Z=J92*XVY(VNO;F9FVJNIJ0,G&V))VAL[ED#/
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H,T,Z325INC=4\=&0]GU`&3XQ:25C9.C3>VX8;4)'&(K%K"";<Z/."V>^&
``
end
size 9805

From cellular-automata-request@Think.COM  Tue Jan 22 10:33:07 1991
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Date: 22 Jan 91 15:25:03 GMT
From: gordon@RPI.EDU (Gordon E. Greene)
Organization: Rensselaer Polytechnic Institute, Troy NY
Subject: Re: Life Wars
Message-Id: <$66^2V+@rpi.edu>
Newsgroups: comp.theory.cell-automata
References: <1991Jan21.190759.3684@midway.uchicago.edu>
Sender: ca-request@Think.COM
To: ca@Think.COM

In article <1991Jan21.190759.3684@midway.uchicago.edu> kawl@quads.uchicago.edu (david john kawliche) writes:
>
>	I have recently written a program (in LSC 4.0, for the mac)
>that allows two 'teams' of cellular automata to be grown in the same
>medium.  The interactions between cells of the same type can be set
...
>in knowing if anyone has done this before, and if there is interest in 
>such a program.

I'd be interested in such a program.
-- 
--------- You can never have too many ferrets. -----------
gordon@rpi.edu    USERF023@RPITSMTS   USERF023@mts.rpi.edu

From cellular-automata-request@Think.COM  Tue Jan 22 11:18:38 1991
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Date: Mon, 21 Jan 91 19:07:09 PST
From: autodesk!air!rudy@fernwood.mpk.ca.us (Rudy Rucker)
Message-Id: <9101220307.AA15488@air.acad>
To: ca@Think.COM
Subject: life wars


In CA Lab ( for the PC ) I looked at several CA worlds which have cells
behaving according to different rules.  Brian Silverman first pointed 
out to me that you can have, e.g. Life and Anti-Life running together,
where Anti-Life treats 0s as 1s and 1s as 0s.  I wrote a different
version of this called Ecolibra in which Life and Silverman's Brain
rule run, depending on the state of a background bit, which bit can be
affected by a high enough activity level of either rule.  In another
foray into the mixed CA mindscape, I wrote the Ranch rule in which 
Vichniac's Vote rule is used to divide the world into yellow and black
cells that group in to gerrymander shapes.  Life runs on the yellow and
Brain runs on the black.  They are symbiotic in that occasionally a
firing cell can move from yellow to black or from black to yellow,
thus restimulating the other rule.  If we use toroidal wrap and have
a start condition such that the yellow and black region wrap into two
bands, then Ranch can maintain a seemingly immortal but pleasing 
damped and various existence.  This is all in the CA Lab manual
, CA Lab can be ordered for $60 by phoning Autodesk at (800)688-2344.

I am curious about how you are deciding which rules to obey at which
cell-sites!

From cellular-automata-request@Think.COM  Tue Jan 22 11:32:17 1991
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Date: 22 Jan 91 12:34:44 GMT
From: angelo@cs.kun.nl (Angelo Melis)
Subject: >Life Wars
Message-Id: <2671@wn1.sci.kun.nl>
Newsgroups: comp.theory.cell-automata
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I have interest in the program.
As I don't have a mac, could you please give the sources.
I will try to port it.

Angelo
e-mail : angelo@cs.kun.nl

From cellular-automata-request@Think.COM  Tue Jan 22 11:34:12 1991
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Date: 22 Jan 91 16:23:47 GMT
From: hiebeler@Think.COM (Dave Hiebeler)
Organization: Thinking Machines Corporation
Subject: Re: Life Wars
Message-Id: <HIEBELER.91Jan22112347@custard.think.com>
Newsgroups: comp.theory.cell-automata
References: <1991Jan21.190759.3684@midway.uchicago.edu>
Sender: ca-request@Think.COM
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> 	I have recently written a program (in LSC 4.0, for the mac)
> that allows two 'teams' of cellular automata to be grown in the same
> medium.  The interactions between cells of the same type can be set
> and so can the interactions between cells of differing types.
> ...
> ... [I] believe that the possiblity for warring, symbiotic,
> segragationalist and other general behaviors are possible. 
> I am interested in knowing if anyone has done this before, and if
> there is interest in such a program.

  Norm Packard did some work on evolving CA rules, and I believe some
"competition" between rules was involved in those experiments,
although I forget the details.  I *think* this was described in the
article "A Learning Algorithm for Modeling Complex Spatial Dynamics"
by Packard, Meyer, and Richards.  However, my files are in storage
right now, so it would be a couple of weeks before I could go check.
Also, I don't know where the article was published.  [If someone could
tell me, I'd appreciate it.]  I'm sure someone will correct me if I'm
wrong here, since Norm's work is very well-known.


  I know Rudy Rucker has done some CA programs (on both the CA Lab PC
software, and the CAM CA coprocessor) where he runs two different
rules on two different bitplanes, and gives a "mask" specifying where
they may interact, as well as some rule for interaction.

  Rucker wrote this up in the following article:
"Symbiotic Programming: Crossbreeding Cellular Automaton Rules on the
CAM-6", in _Complex Systems_ journal, vol. 3, 1989 (pp 79-90).


  I'm sure there have been others, that I'm forgetting right now.

  I've done a little bit of work with Chris Langton's "vants", or
"virtual ants".  (See "Studying Artificial Life with Cellular
Automata", by C. Langton, in Physica D, vol. 22, 1986 (pp. 120-149)).
I extended the notion by experimented with two different types of
vants, whose behaviors were essentially "mirror images" of each other,
with some specification for the interactions between the two different
types.  I found that the behavior with 2 types of vants was
significantly more interesting than the behavior with only 1 type.  I
haven't written anything up about it, and haven't fiddled with it for
quite a while now.  I had these running both on a CAM, and on a
Connection Machine.

--
Dave Hiebeler                  | Internet: hiebeler@think.com
Thinking Machines Corporation  | Phone:  (617) 234-4070 (work)
245 First Street               | "Off we go, into the wilds you ponder."
Cambridge, MA 02142            |

From cellular-automata-request@Think.COM  Thu Jan 24 11:35:48 1991
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Date: 24 Jan 91 15:38:17 GMT
From: lwyse@kendall.bu.edu (Lonce LaMar Wyse)
Organization: Boston University Center for Adaptive Systems
Subject: mailing list
Message-Id: <LWYSE.91Jan24103817@kendall.bu.edu>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
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Last year there was an announcement of a mailing list for people doing
research in genetic algs and artificial life. I beleive it was based
in Illinois or somewhere in the mid-west. Does anybody know about
this?

					Thanks, Lonce

   XXX     XXX         Lonce Wyse                                |
  X           X        Center for Adaptive Systems          \    |    /
  X           X        Boston University                     \       /
                       111 Cummington St.                   
                       Boston,MA 02215                   ----         ----
  X           X                                   
  X           X        "The best things in life              /       \
   XXX     XXX         are emergent."                       /    |    \
                                                                 |


From bmb@Think.COM  Thu Jan 24 11:41:51 1991
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To: lwyse@kendall.bu.edu
Cc: ca@Think.COM, bmb@Think.COM
In-Reply-To: Lonce LaMar Wyse's message of 24 Jan 91 15:38:17 GMT <LWYSE.91Jan24103817@kendall.bu.edu>
Subject: mailing list


   Date: 24 Jan 91 15:38:17 GMT
   From: lwyse@kendall.bu.edu (Lonce LaMar Wyse)


   Last year there was an announcement of a mailing list for people doing
   research in genetic algs and artificial life. I beleive it was based
   in Illinois or somewhere in the mid-west. Does anybody know about
   this?

					   Thanks, Lonce

      XXX     XXX         Lonce Wyse                                |
     X           X        Center for Adaptive Systems          \    |    /
     X           X        Boston University                     \       /
			  111 Cummington St.                   
			  Boston,MA 02215                   ----         ----
     X           X                                   
     X           X        "The best things in life              /       \
      XXX     XXX         are emergent."                       /    |    \
								    |

This is probably what you're looking for:

=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=---=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
=                      Artificial Life Distribution List                  =
=                                                                         =
=      All submissions for distribution to: alife@iuvax.cs.indiana.edu    =
= All list subscriber additions, deletions, or administrative details to: =
=                    alife-request@iuvax.cs.indiana.edu                   =
=         All software, tech reports to Alife depository through          =
=         anonymous ftp at iuvax.cs.indiana.edu in ~ftp/pub/alife         =
=                                                                         =
=     List maintainers: Elisabeth Freeman, Eric Freeman, Marek Lugowski   =
=           Artificial Life Research Group, Indiana University            =
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=---=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=

--Bruce Boghosian

From cellular-automata-request@Think.COM  Thu Jan 24 11:48:33 1991
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	id AA03335; Thu, 24 Jan 91 09:47:15 MST
Date: Thu, 24 Jan 91 09:47:15 MST
From: cgl%t13@LANL.GOV (Chris Langton)
Message-Id: <9101241647.AA03335@t13.lanl.gov.>
To: ca@Think.COM
Subject: Artificial Life mailing list

Here is the info on the Alife mailing list:

=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=---=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
=                      Artificial Life Distribution List                  =
=                                                                         =
=      All submissions for distribution to: alife@iuvax.cs.indiana.edu    =
= All list subscriber additions, deletions, or administrative details to: =
=                    alife-request@iuvax.cs.indiana.edu                   =
=         All software, tech reports to Alife depository through          =
=         anonymous ftp at iuvax.cs.indiana.edu in ~ftp/pub/alife         =
=                                                                         =
=     List maintainers: Elisabeth Freeman, Eric Freeman, Marek Lugowski   =
=           Artificial Life Research Group, Indiana University            =
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=---=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=

Cheers!

Chris Langton

Complex Systems Group
MS B213, Theoretical Division		Phone: 505-667-9471
Los Alamos National Laboratory		Email: cgl@t13.lanl.gov
Los Alamos, New Mexico, USA
87545








From cellular-automata-request@Think.COM  Mon Jan 28 16:27:11 1991
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Date: 28 Jan 91 20:35:08 GMT
From: fontenot@rice.edu (Dwayne Jacques Fontenot)
Organization: Rice University, Houston, Texas
Subject: source for Gosper's Hashlife
Message-Id: <1991Jan28.203508.27886@rice.edu>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM

Hello,

Does anyone know where I can get some source or a pseudo-code algorithm
for Bill Gosper's "Hashlife"?

The information I have says that the hashlife algorithm was designed in 1982
and that it uses self-referential hash tables to store lookup patterns for
John Conway's game of life. The algorithm is somewhat adaptive in that it
"learns" which patterns to store and works up from relatively small patterns
(4 x 4) to arbitrarily large ones.

As you might deduce from the above, the algorithm starts out slowly and then
accelerates logarithmically. I deduce that it uses memory in the same way ;-)

The algorithm has the intriguing property of storing, in the hash table, all
the information to recreate the life universe at any time in its history.
Gosper was described as running backwards and forwards in time to see how
interesting forms were produced.

The description I saw (in the book, Mind Children) was not complete enough
(in my opinion, anyway) for me to implement the alogorithm.
I would like to implement this algorithm, but I believe I need a better
description than was given in the book. Source code of any kind would be
even better...

Thank you for your time,

Dwayne Fontenot
fontenot@uncle-bens.rice.edu

From cellular-automata-request@Think.COM  Mon Jan 28 17:03:36 1991
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Date: Mon, 28 Jan 91 15:03:29 MST
From: cgl%t13@LANL.GOV (Chris Langton)
Message-Id: <9101282203.AA11743@t13.lanl.gov.>
To: ca@Think.COM
Subject: Gosper's ``hash-life'' algorithm....


   For a better description of the algorithm Gosper used, see his chapter
``Exploiting regularities in Large Cellular Spaces'' in the book: Cellular
Automata, edited by Farmer, Toffoli, and Wolfram, published by North Holland
in 1984. This was a book version of the proceedings of the 1983 CA conference
at Los Alamos, originally published as a special issue of the Journal Physica-D.
The original citation is: Physica 10D, (1984) pp.75-80.  There are many other
interesting articles on CA's in this volume as well...., especially those by
Toffoli, Margolus, Vichniac, Grassberger, and Wolfram.

  Unfortunately, I don't recall any source code for Gosper's algorithm being
included in his article...


Cheers!

Chris Langton

Complex Systems Group
MS B213, Theoretical Division		Phone: 505-667-9471
Los Alamos National Laboratory		Email: cgl@t13.lanl.gov
Los Alamos, New Mexico, USA
87545




From cellular-automata-request@Think.COM  Fri Feb  1 23:26:56 1991
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Date: 1 Feb 91 06:55:43 GMT
From: becker!bdb@bloom-beacon.MIT.EDU (Bruce D. Becker)
Organization: G. T. S., Toronto, Ontario, Canada
Subject: Re: Life Wars
Message-Id: <70327@becker.UUCP>
Newsgroups: comp.theory.cell-automata
References: <1991Jan21.190759.3684@midway.uchicago.edu>
Sender: ca-request@Think.COM
To: ca@Think.COM

In article <1991Jan21.190759.3684@midway.uchicago.edu> kawl@quads.uchicago.edu (david john kawliche) writes:
|
|	I have recently written a program (in LSC 4.0, for the mac)
|that allows two 'teams' of cellular automata to be grown in the same
|medium.  The interactions between cells of the same type can be set
|and so can the interactions between cells of differing types.  I have 
|gotten some very interseting results in the first few passes at this sort
|of simulation and believe that the possiblity for warring, symbiotic, 
|segragationalist and other general behaviors are possible.  I am interested
|in knowing if anyone has done this before, and if there is interest in 
|such a program.

	Such a program was done a couple of years ago
	for the Amiga by Chuck McManis. The source was
	sold as a demo of the use of as many Amiga
	functions as could be put in a program, mostly
	for programmer education. Nevertheless, the
	program was quite interesting as well as being
	visually attractive...

-- 
  ,u,	 Bruce Becker	Toronto, Ontario
a /i/	 Internet: bdb@becker.UUCP, bruce@gpu.utcs.toronto.edu
 `\o\-e	 UUCP: ...!uunet!mnetor!becker!bdb
 _< /_	 "Que es mas macho: moral fiber, o oat bran?" - lala

From cellular-automata-request@Think.COM  Sun Feb  3 13:57:48 1991
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Date: Sun, 3 Feb 91 11:57:35 MST
From: cgl@t13.lanl.gov (Chris Langton)
Message-Id: <9102031857.AA27979@t13.lanl.gov.>
To: ca@Think.COM
Subject: Re: Life Wars and studies of same in various extensions of CA's

In article <1991Jan21.190759.3684@midway.uchicago.edu> kawl@quads.uchicago.edu 
(david john kawliche) writes:

|
|	I have recently written a program (in LSC 4.0, for the mac)
|that allows two 'teams' of cellular automata to be grown in the same
|medium.  The interactions between cells of the same type can be set
|and so can the interactions between cells of differing types.  I have 
|gotten some very interseting results in the first few passes at this sort
|of simulation and believe that the possiblity for warring, symbiotic, 
|segragationalist and other general behaviors are possible.  I am interested
|in knowing if anyone has done this before, and if there is interest in 
|such a program.

  From the earliest days of CA research, there have been many CA rules
and systems studied which give rise to such life-like behavior,
which is one of the reasons CA have played a large role in the field
of Artificial Life.

  The earliest work, of course, goes back to von Neumann and Ulam.
Von Neumann discusses this possibility in The Theory of Self-Reproducing
Automata, Ed. A.W. Burks (1966). There are several articles by Stan
Ulam on competition between CA patterns in Burks' collection: Essays
on Cellular Automata (1970). 

  Note that the distinction between competing patterns and competing 
rules is not a clean one, because different rules can be collected together 
in one larger rule, and different patterns can be seen as invoking different 
"subrules" of one CA rule. 

  Systems which can be viewed as extensions to CA which involve a cleaner 
(but still not necessarliy complete) distinction between patterns and rules 
have been devised. John Holland had several articles in Burks' collection 
involving such systems. Richard Laing - a long-time member of Burks' Logic of 
Computers Group at U. Michigan - devised a system involving what he called 
Molecular Automata, which would interact with each other in the context of a 
"soup" of such machines, much like a beaker full of reactive enzymes and 
substrates.

   More recently, Lugowski and company at U. of Indiana have been developing
a system they refer to as a Computational Metabolism, which is much
like a CA in which the cells are no longer nailed-down to particular lattice
positions and can migrate around the lattice, interacting with other cells 
under control of an internal state-transition function. These cells are
much more complex than traditional CA cells - and are reminiscient of John 
Hollands iterative circuit computers, described in the articles mentioned 
above.

  A system involving Movable Finite Automata (MFA) has been developed by 
Narendra Goel and Richard Thompson and successfully applied to a number of
biological problems, including the self-assembly of a T4-phage virus.
In this sytem, the "cells" are also free to move about and have complex
internal state machines, which are connected to "sensors" and "effectors"
on the cell's surfaces. These sensors and effectors are fairly general
purpose, but have been used to mimic molecular recognition and bonding sites.
The MFA machines are typically driven about a 3-D volume by diffusion. 

  Walter Fontanna and Steen Rasmussen at Los Alamos and Tom Ray at U. Deleware
are developing what might be called "artificial-chemistries" or "computational 
chemistries", in which the reaction-logic of real chemistries is abstracted to 
a logic of interacting algorithms or pure lisp functions. Competition, selection,
symbiotism, complex ecological dynamics, evolutionary progress, and much more 
are seen in such systems. 

  With a team at UCLA, we are developing a system for the Connection Machine
which we are calling a "process-gas" - an object oriented system in which 
a large collection of arbitrarily programmable processes move around within
the space of processors, interacting with each other and with local 
environmental objects, which are also programmable. This system should be 
general enough to allow the investigation of the whole hierarchy of biological 
phenomena, from molecule-molecule interactions to evolving eco-systems. To
date, it has been partially implemented by Rob Collins at UCLA, and applied
to the study of ant-colony dynamics, in which up to a million or so "ants" 
(neural-net-driven objects) swarm around inside the CM2, interacting and 
competing with each other to collect "food" and return it to their nests.

  In general, many of these CA-extensions are well-suited to the study of 
biological phenomena because they all share an underlying architecture that 
captures the basic architecture of most biological phenomena: a huge number 
of semi-autonomous parts engaged in local interactions with one another according 
to their own individual behavioral repertoires in the context of a complex 
environment. All of this takes place *IN THE ABSENCE OF A CENTRAL CONTROLLER*! 
I.e., these systems are "bottom-up" as opposed to "top-down" - as are CA - and 
I argue (although many disagree) that they allow, in principle anyway, the 
actual synthesis of biological phenomena in computers, something which goes 
beyond mere simulation.

  A feature which distinguishes many of these systems from CA's is that the
researcher specifies behavioral rules at the level of the "object", rather
than at the level of the lattice. Although in principle CA with large 
state sets can be though of in this way, it is much easier to work from
the perspective of the objects which interact in the system than it is to work 
from the perspective of the lattice in which the objects interact. For problems 
in which the study of the latter is important (such as reaction-difusion
systems), CA are great. But having to work out the kinetics of moving objects
covering many CA sites is quite a chore, and for the study of such things as
ecosystem dynamics, the low-level physics of movement is irrelevant to the 
behavior of interest, and movement can be finessed in simpler ways, without
affecting the behaviors that the researcher is interested in studying.

  I would be interested in seeing discussions of such CA-extensions in 
this group in addition to discussions of CA themselves. Much of what
makes us interested in CA is retained in such systems: they are bottom-up, 
spatially distributed collections of processes interacting with one another.
They are like CA in which the cells are free to move about - or equivalently -
in which the contents of cells are free to move about if one insists on
keeping the cells themselves fixed. They may involve alterations to the basic 
CA paradigm, such as allowing continuous representations of space or state 
instead of discrete ones, or allowing for arbitrarily powerful computing 
machines within each "cell".

  Some representations are more suited to the study of certain natural phenomena
than others. I have found CA very useful for some problems but unmanageable
for others which could, in principle, be studied by CA. All seem to capture
that essential CA feature of allowing the study of hierarchies of "emergent" 
global dynamics.  

  So, how about it? What CA-like systems have others worked with and found 
useful? What research topics are they addressing?What research topics are they addressing?

Cheers!

Chris Langton

Complex Systems Group
MS B213, Theoretical Division		Phone: 505-667-9471
Los Alamos National Laboratory		Email: cgl@t13.lanl.gov

From cellular-automata-request@Think.COM  Mon Feb  4 09:30:42 1991
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Date: Mon, 4 Feb 91 07:16:10 MST
From: cgl@infidel.LANL.GOV (Chris Langton)
Message-Id: <9102041416.AA11875@infidel.lanl.gov>
To: ca@Think.COM
Subject: Cellsim Bug Fix



Cellsim Bug Fix

========

This message is to announce the availability of a patch for Cellsim,
which fixes a problem encountered when running under SunOS 4.1 or newer.
The patch itself is appended at the end of this message.

This bug causes cellsim to hang --- and freezes the whole window system ---
if the cursor is moved out of the control panel while a run is in progress.

Cellsim Distribution List
-------------------------

This message is being sent to the CA mail-list. We are maintaining a Cellsim
distribution list, in order to keep Cellsim users up to date on new
releases and bug fixes. If you would like to be on this list, please
send a message to cgl@t13.lanl.gov. You will get two copies of this message
if you are on both lists - sorry!

For those unfamiliar with Cellsim
---------------------------------

  Cellsim is a SunView-based cellular automata simulator, which can run
on a lattice of size up to 512x512.  It can perform calculations
locally on a Sun workstation, or on a Connection Machine supercomputer
(either directly or through the network).  On the CM, it is possible
to do some non-CA extensions, such as floating-point calculations and
so on.  And of course, you'll get some fantastic speed on the CM.

  Cellsim is still available for anonymous FTP, from
archive.cs.rpi.edu (128.213.10.18), in the directory "cellsim".  The
tarfile "cellsim_2.5.tar.Z" contains the latest version of Cellsim,
V2.5  There are also some patches available in subdirectories there,
but the tarfile currently available has ALREADY HAD THE PATCHES
INSTALLED.  (Sorry to shout, but I want to be sure no one misses that).


The future of Cellsim
---------------------

  Cellsim was written by a few different authors, and the source-code is
really pretty ugly and getting hard to maintain at this point.  I am
planning on eventually releasing a new, totally rewritten version,
that will probably run under X-windows (but which will be much easier
to port to other platforms than Cellsim is).

One of my main motivations for doing so is to take advantage of
several ideas I have for optimizing the calculations on the Connection
Machine, and taking advantage of some of the CM's features that are
not tapped into by the current Cellsim.  I realize that not everyone
has access to a CM, so future Cellsims will still be able to run the
calculations locally as well.


The problem and the patch
-------------------------

  Many people have noticed a pretty terrible bug in Cellsim, when
running on SunOS 4.1 or newer.  The problem is that, if you start
running a rule, and move the mouse cursor outside of the Cellsim
window while the rule is running, SunView will essentially hang.  You
won't be able to select any other windows, or stop the run by clicking
on the left mouse-button as you should be able to.

**NOTE: You should install this patch, even if you don't yet use SunOS
4.1, since in the future you may upgrade, and it's best to be
prepared.  Also, any future patches to Cellsim may rely on this one
being already installed.

  With the help of someone at Sun (Matthew Stier, to whom I am *very*
grateful for his help), I've fixed the problem in Cellsim.
Apparently, something was changed in the event-handler or notifier in
the SunView libraries when 4.1 came out.  Actually, I'm not sure if
Cellsim *should* have worked even under 3.5 -- it may have been using
an undocumented property of SunView.  I'm not familiar enough with the
low-level details of SunView, and I didn't write that part of Cellsim,
so I'm not sure about it.

  Three routines in the "cellscr.c" file need to be changed, to fix
the problem.  These routines are check_button(), set_run_mode(), and
unset_run_mode().

  I've appended a patch at the end of this message, which you can
apply to your copy of cellscr.c (you will then need to recompile
Cellsim).  To use the patch, save everything between the "==cut here=="
labels into a file.  Assuming you call the file "4.1_patchfile", in the
same directory with cellscr.c, you can apply the patch by doing:

              patch cellscr.c 4.1_patchfile

You should see a message indicating that 2 hunks succeeded.
Patch will make a backup copy of your original cellscr.c, called
"cellscr.c.orig", and will create a new, modified cellscr.c with the
patches installed.  You should then be able to recompile Cellsim.

  If you don't have the "patch" command, you can get a copy of the
three routines that were modified, via one of 2 methods:

 1. Through anonymous FTP to archive.cs.rpi.edu (128.213.10.18).  Use
    the login name "anonymous", and your e-mail address as a password.
    Look in the directory "cellsim/patch2", for a file named
    "4.1_cellscr.c".  You can replace your "cellscr.c" file with this
    version, assuming you haven't made any local changes to your
    cellscr.c.

    If you *have* modified your cellscr.c file already, then you should get
    the file "4.1_functions".  This file contains only the three functions
    that were changed.  You should manually replace the old versions of
    these routines in your cellscr.c file with these new versions.

    The patchfile is also in the FTP archive, although you shouldn't
    need it, since it's appended below.

 2. If you aren't able to FTP, then send me a note requesting either
    of the above files, and I will send it to you.  I'm awfully busy
    lately, so please use FTP if you can.


A linker bug
------------

  Some people are encountering linker errors when trying to load in
computed-function rules (getting "ld: -T" errors).  I haven't figured
this one out yet -- hopefully soon.  Actually, someone else had that
problem more than a year ago, and we solved it then.  The problem is,
I don't remember how we solved it, and I've moved so many times since
then, I can't find the bug-report where I recorded the solution!  If
the person who had this problem is reading this, and remembers how we
fixed it, could you please let me know?  Thanks.  :-)

  I realize I probably should have waited and fixed both bugs at once
with one patch, but the SunView problem is so severe, I wanted to make
this patch available as soon as possible.  Also, I don't know if many
people are encountering the linker problem; it seems pretty rare.


Disclaimer
----------

  I feel I better add this -- despite the fact that it is a tool for
doing computations on the Connection Machine (and Sun workstations),
Cellsim is in no way supported by Thinking Machines Corporation.  I
worked on Cellsim for quite some time before joining TMC.  If you have
any questions/comments/complaints about Cellsim, please direct them to
me (hiebeler@think.com) or Chris Langton (cgl@t13.lanl.gov), and not to
Thinking Machines Corporation or Los Alamos National Laboratory.


Here is the patch, below.  Use everything between the "===cut here==="
delimiters (there is one at both ends -- don't forget to delete my
signature at the end).

===cut here===
*** cellscr_orig.c	Thu Jan 31 08:36:19 1991
--- cellscr.c	Thu Jan 31 08:39:09 1991
***************
*** 1707,1723 ****
  
  set_run_mode()
  {					/* disable panel & canvas input */
-     int     fd;				/* window file descriptor */
  
      frame_mask = *((Inputmask *) window_get(frame, WIN_PICK_INPUT_MASK));
!     window_set(frame, WIN_CONSUME_PICK_EVENT, MS_LEFT, 0);
      panel_mask = *((Inputmask *) window_get(panel, WIN_PICK_INPUT_MASK));
!     window_set(panel, WIN_CONSUME_PICK_EVENT, WIN_NO_EVENTS, 0);
      canvas_mask = *((Inputmask *) window_get(canvas, WIN_PICK_INPUT_MASK));
!     window_set(canvas, WIN_CONSUME_PICK_EVENT, WIN_NO_EVENTS, 0);
!     fd = (int) window_get(frame, WIN_FD);
!     fcntl(fd, F_SETFL, FNDELAY);
!     /* set non-blocking mode */
  }
  
  
--- 1707,1719 ----
  
  set_run_mode()
  {					/* disable panel & canvas input */
  
      frame_mask = *((Inputmask *) window_get(frame, WIN_PICK_INPUT_MASK));
!     window_set(frame, WIN_CONSUME_PICK_EVENT, WIN_NO_EVENTS, 0);
      panel_mask = *((Inputmask *) window_get(panel, WIN_PICK_INPUT_MASK));
!     window_set(panel, WIN_CONSUME_PICK_EVENT, MS_LEFT, 0);
      canvas_mask = *((Inputmask *) window_get(canvas, WIN_PICK_INPUT_MASK));
!     window_set(canvas, WIN_CONSUME_PICK_EVENT, MS_LEFT, 0);
  }
  
  
***************
*** 1732,1746 ****
  check_button()
  {					/* return TRUE iff the left button has
  					 * been pressed */
!     int     err, button;
      Event   event;
!     do {				/* check all events in pending queue */
! 	err = window_read_event(frame, &event);
! 	button = ((err == 0) && (event_is_up(&event)) &&
  		  (event_id(&event) == MS_LEFT));
!     } while ((err == 0) && !button);
      /* if no events remain, err will equal -1 */
!     return (button);
  }
  
  
--- 1728,1762 ----
  check_button()
  {					/* return TRUE iff the left button has
  					 * been pressed */
!     int     err, button1, button2;
!     int fd1, ff1, fd2, ff2;
      Event   event;
! 
!     /* set non-blocking mode in panel */
!     fd1 = (int) window_get(panel, WIN_FD);
!     ff1 = fcntl(fd1, F_GETFL, 0);
!     fcntl(fd1, F_SETFL, FNDELAY);
!     /* non-blocking mode in canvas */
!     fd2 = (int) window_get(canvas, WIN_FD);
!     ff2 = fcntl(fd2, F_GETFL, 0);
!     fcntl(fd2, F_SETFL, FNDELAY);
!     do {
! 	err = window_read_event(panel, &event);
! 	button1 = ((err == 0) && (event_is_up(&event)) &&
  		  (event_id(&event) == MS_LEFT));
!     } while ((err == 0) && !button1);
!     do {
! 	err = window_read_event(canvas, &event);
! 	button2 = ((err == 0) && (event_is_up(&event)) &&
! 		  (event_id(&event) == MS_LEFT));
!     } while ((err == 0) && !button2);
      /* if no events remain, err will equal -1 */
! 
!     /* Restore blocking mode in panel and canvas */
!     fcntl(fd1, F_SETFL, ff1);
!     fcntl(fd2, F_SETFL, ff2);
!     /* if button was pressed in either panel or canvas, return 1 */
!     return (button1 | button2);
  }
  
  
===cut here===

--
Dave Hiebeler                  | Internet: hiebeler@think.com
Thinking Machines Corporation  | Phone:  (617) 234-4070 (work)
245 First Street               |
Cambridge, MA 02142  USA       |


From cellular-automata-request@Think.COM  Mon Feb  4 11:24:28 1991
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	id AA14310; Mon, 4 Feb 91 07:16:19 -0700
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	id AA11875; Mon, 4 Feb 91 07:16:10 MST
Date: Mon, 4 Feb 91 07:16:10 MST
From: cgl@infidel.LANL.GOV (Chris Langton)
Message-Id: <9102041416.AA11875@infidel.lanl.gov>
To: ca@Think.COM
Subject: Cellsim Bug Fix



Cellsim Bug Fix

========

This message is to announce the availability of a patch for Cellsim,
which fixes a problem encountered when running under SunOS 4.1 or newer.
The patch itself is appended at the end of this message.

This bug causes cellsim to hang --- and freezes the whole window system ---
if the cursor is moved out of the control panel while a run is in progress.

Cellsim Distribution List
-------------------------

This message is being sent to the CA mail-list. We are maintaining a Cellsim
distribution list, in order to keep Cellsim users up to date on new
releases and bug fixes. If you would like to be on this list, please
send a message to cgl@t13.lanl.gov. You will get two copies of this message
if you are on both lists - sorry!

For those unfamiliar with Cellsim
---------------------------------

  Cellsim is a SunView-based cellular automata simulator, which can run
on a lattice of size up to 512x512.  It can perform calculations
locally on a Sun workstation, or on a Connection Machine supercomputer
(either directly or through the network).  On the CM, it is possible
to do some non-CA extensions, such as floating-point calculations and
so on.  And of course, you'll get some fantastic speed on the CM.

  Cellsim is still available for anonymous FTP, from
archive.cs.rpi.edu (128.213.10.18), in the directory "cellsim".  The
tarfile "cellsim_2.5.tar.Z" contains the latest version of Cellsim,
V2.5  There are also some patches available in subdirectories there,
but the tarfile currently available has ALREADY HAD THE PATCHES
INSTALLED.  (Sorry to shout, but I want to be sure no one misses that).


The future of Cellsim
---------------------

  Cellsim was written by a few different authors, and the source-code is
really pretty ugly and getting hard to maintain at this point.  I am
planning on eventually releasing a new, totally rewritten version,
that will probably run under X-windows (but which will be much easier
to port to other platforms than Cellsim is).

One of my main motivations for doing so is to take advantage of
several ideas I have for optimizing the calculations on the Connection
Machine, and taking advantage of some of the CM's features that are
not tapped into by the current Cellsim.  I realize that not everyone
has access to a CM, so future Cellsims will still be able to run the
calculations locally as well.


The problem and the patch
-------------------------

  Many people have noticed a pretty terrible bug in Cellsim, when
running on SunOS 4.1 or newer.  The problem is that, if you start
running a rule, and move the mouse cursor outside of the Cellsim
window while the rule is running, SunView will essentially hang.  You
won't be able to select any other windows, or stop the run by clicking
on the left mouse-button as you should be able to.

**NOTE: You should install this patch, even if you don't yet use SunOS
4.1, since in the future you may upgrade, and it's best to be
prepared.  Also, any future patches to Cellsim may rely on this one
being already installed.

  With the help of someone at Sun (Matthew Stier, to whom I am *very*
grateful for his help), I've fixed the problem in Cellsim.
Apparently, something was changed in the event-handler or notifier in
the SunView libraries when 4.1 came out.  Actually, I'm not sure if
Cellsim *should* have worked even under 3.5 -- it may have been using
an undocumented property of SunView.  I'm not familiar enough with the
low-level details of SunView, and I didn't write that part of Cellsim,
so I'm not sure about it.

  Three routines in the "cellscr.c" file need to be changed, to fix
the problem.  These routines are check_button(), set_run_mode(), and
unset_run_mode().

  I've appended a patch at the end of this message, which you can
apply to your copy of cellscr.c (you will then need to recompile
Cellsim).  To use the patch, save everything between the "==cut here=="
labels into a file.  Assuming you call the file "4.1_patchfile", in the
same directory with cellscr.c, you can apply the patch by doing:

              patch cellscr.c 4.1_patchfile

You should see a message indicating that 2 hunks succeeded.
Patch will make a backup copy of your original cellscr.c, called
"cellscr.c.orig", and will create a new, modified cellscr.c with the
patches installed.  You should then be able to recompile Cellsim.

  If you don't have the "patch" command, you can get a copy of the
three routines that were modified, via one of 2 methods:

 1. Through anonymous FTP to archive.cs.rpi.edu (128.213.10.18).  Use
    the login name "anonymous", and your e-mail address as a password.
    Look in the directory "cellsim/patch2", for a file named
    "4.1_cellscr.c".  You can replace your "cellscr.c" file with this
    version, assuming you haven't made any local changes to your
    cellscr.c.

    If you *have* modified your cellscr.c file already, then you should get
    the file "4.1_functions".  This file contains only the three functions
    that were changed.  You should manually replace the old versions of
    these routines in your cellscr.c file with these new versions.

    The patchfile is also in the FTP archive, although you shouldn't
    need it, since it's appended below.

 2. If you aren't able to FTP, then send me a note requesting either
    of the above files, and I will send it to you.  I'm awfully busy
    lately, so please use FTP if you can.


A linker bug
------------

  Some people are encountering linker errors when trying to load in
computed-function rules (getting "ld: -T" errors).  I haven't figured
this one out yet -- hopefully soon.  Actually, someone else had that
problem more than a year ago, and we solved it then.  The problem is,
I don't remember how we solved it, and I've moved so many times since
then, I can't find the bug-report where I recorded the solution!  If
the person who had this problem is reading this, and remembers how we
fixed it, could you please let me know?  Thanks.  :-)

  I realize I probably should have waited and fixed both bugs at once
with one patch, but the SunView problem is so severe, I wanted to make
this patch available as soon as possible.  Also, I don't know if many
people are encountering the linker problem; it seems pretty rare.


Disclaimer
----------

  I feel I better add this -- despite the fact that it is a tool for
doing computations on the Connection Machine (and Sun workstations),
Cellsim is in no way supported by Thinking Machines Corporation.  I
worked on Cellsim for quite some time before joining TMC.  If you have
any questions/comments/complaints about Cellsim, please direct them to
me (hiebeler@think.com) or Chris Langton (cgl@t13.lanl.gov), and not to
Thinking Machines Corporation or Los Alamos National Laboratory.


Here is the patch, below.  Use everything between the "===cut here==="
delimiters (there is one at both ends -- don't forget to delete my
signature at the end).

===cut here===
*** cellscr_orig.c	Thu Jan 31 08:36:19 1991
--- cellscr.c	Thu Jan 31 08:39:09 1991
***************
*** 1707,1723 ****
  
  set_run_mode()
  {					/* disable panel & canvas input */
-     int     fd;				/* window file descriptor */
  
      frame_mask = *((Inputmask *) window_get(frame, WIN_PICK_INPUT_MASK));
!     window_set(frame, WIN_CONSUME_PICK_EVENT, MS_LEFT, 0);
      panel_mask = *((Inputmask *) window_get(panel, WIN_PICK_INPUT_MASK));
!     window_set(panel, WIN_CONSUME_PICK_EVENT, WIN_NO_EVENTS, 0);
      canvas_mask = *((Inputmask *) window_get(canvas, WIN_PICK_INPUT_MASK));
!     window_set(canvas, WIN_CONSUME_PICK_EVENT, WIN_NO_EVENTS, 0);
!     fd = (int) window_get(frame, WIN_FD);
!     fcntl(fd, F_SETFL, FNDELAY);
!     /* set non-blocking mode */
  }
  
  
--- 1707,1719 ----
  
  set_run_mode()
  {					/* disable panel & canvas input */
  
      frame_mask = *((Inputmask *) window_get(frame, WIN_PICK_INPUT_MASK));
!     window_set(frame, WIN_CONSUME_PICK_EVENT, WIN_NO_EVENTS, 0);
      panel_mask = *((Inputmask *) window_get(panel, WIN_PICK_INPUT_MASK));
!     window_set(panel, WIN_CONSUME_PICK_EVENT, MS_LEFT, 0);
      canvas_mask = *((Inputmask *) window_get(canvas, WIN_PICK_INPUT_MASK));
!     window_set(canvas, WIN_CONSUME_PICK_EVENT, MS_LEFT, 0);
  }
  
  
***************
*** 1732,1746 ****
  check_button()
  {					/* return TRUE iff the left button has
  					 * been pressed */
!     int     err, button;
      Event   event;
!     do {				/* check all events in pending queue */
! 	err = window_read_event(frame, &event);
! 	button = ((err == 0) && (event_is_up(&event)) &&
  		  (event_id(&event) == MS_LEFT));
!     } while ((err == 0) && !button);
      /* if no events remain, err will equal -1 */
!     return (button);
  }
  
  
--- 1728,1762 ----
  check_button()
  {					/* return TRUE iff the left button has
  					 * been pressed */
!     int     err, button1, button2;
!     int fd1, ff1, fd2, ff2;
      Event   event;
! 
!     /* set non-blocking mode in panel */
!     fd1 = (int) window_get(panel, WIN_FD);
!     ff1 = fcntl(fd1, F_GETFL, 0);
!     fcntl(fd1, F_SETFL, FNDELAY);
!     /* non-blocking mode in canvas */
!     fd2 = (int) window_get(canvas, WIN_FD);
!     ff2 = fcntl(fd2, F_GETFL, 0);
!     fcntl(fd2, F_SETFL, FNDELAY);
!     do {
! 	err = window_read_event(panel, &event);
! 	button1 = ((err == 0) && (event_is_up(&event)) &&
  		  (event_id(&event) == MS_LEFT));
!     } while ((err == 0) && !button1);
!     do {
! 	err = window_read_event(canvas, &event);
! 	button2 = ((err == 0) && (event_is_up(&event)) &&
! 		  (event_id(&event) == MS_LEFT));
!     } while ((err == 0) && !button2);
      /* if no events remain, err will equal -1 */
! 
!     /* Restore blocking mode in panel and canvas */
!     fcntl(fd1, F_SETFL, ff1);
!     fcntl(fd2, F_SETFL, ff2);
!     /* if button was pressed in either panel or canvas, return 1 */
!     return (button1 | button2);
  }
  
  
===cut here===

--
Dave Hiebeler                  | Internet: hiebeler@think.com
Thinking Machines Corporation  | Phone:  (617) 234-4070 (work)
245 First Street               |
Cambridge, MA 02142  USA       |


From cellular-automata-request@Think.COM  Mon Feb  4 14:26:44 1991
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Date: Mon, 4 Feb 91 10:37:33 PST
From: autodesk!air!rudy@fernwood.mpk.ca.us (Rudy Rucker)
Message-Id: <9102041837.AA01135@air.acad>
To: ca@Think.COM
Subject: Life Wars, Ants

Chris Langton writes the following:

> I would be interested in seeing discussions of such CA-extensions in
> this group in addition to discussions of CA themselves. Much of what
> makes us interested in CA is retained in such systems: they are 
> bottom-up, spatially distributed collections of processes interacting 
> with one another. They are like CA in which the cells are free to move 
> about - or equivalently -in which the contents of cells are free to 
> move about if one insists on keeping the cells themselves fixed. They 
> may involve alterations to the basic CA paradigm, such as allowing 
> continuous representations of space or state instead of discrete ones,
> or allowing for arbitrarily powerful computing machines within each 
> "cell".                         

	Here is some information about experiments of this nature which 
I've been carrying out with so-called ants programs.  In an ants program,
you have a population of program objects which are displayed as moving
graphics icons.  In my experiments, an ant is a C++ object which has:
(x,y): position, (vx,vy): pixels-per-update velocity, s :a running score,
*move : a pointer to a function which computes the ant's next velocity
vector, *eat : a pointer to a function which changes the ant's 
score on the basis of what it encounters, and gene : an array of
"genetic" information that is used in computing the move function.
	Following a suggestion that was made at the A Life II conference,
I normally group my ants into colonies.  On the PC, it is practical to
have something like seven colonies of seven ants each.  At the end of 
each "antyear" (perhaps 2000 update cycles), the ants within each colony
compare their scores to their fellow colony members and are ranked.  The
worst two ants in a colony have their genes replaced by new gene
arrays derived from the genes of the best two ants.  Usually the 
third worst ant's genes are totally randomized as well.  This process
is carried out separately for each colony.  Very clear evolutionary
effects are seen.
	Intercolony evolutionary effects can be achieved by, for instance,
having the less successful colonies use a higher mutation rate.
	So far I have experimented with two general kinds of move
functions.  The simpler approach is based on Micahel  Palmiter's 
"Simulated Evolution" as described in K. Dewdney's recent anthology 
of columns, The Magic Machine (Freeman, 1990).  Here the ants move in
one of six planar directions.  At each update, each ant uses a randomizer
and a private table of probabilities to decide how many degrees to
turn.  If food is scarce, widely spread, and of positive weight, these
ants will evolve to turn rarely and travel in straight lines.  If the
food is concentrated in one region the ants will evolve to turn a lot,
and so on.
	A more interesting kind of antworld arises if we have our ants
move like 2-Dimensional Turing machines.  This paradigm was first 
explored by Langton in a CA setting, where he called them "vants."
Vants are also discussed in Dewdney's book, where he calls them
"turmites," and runs them as separate objects rather than as CAs.  In
my turmite/vant experiments, I allow the ants to move in up to 128
different directions.  Each ant has an internal state, (I've tried up
to 256 states, although very rich behavior already happens with 4
states).  Each colony of ants has a distincitve color of "trail" that
is lays down.  An ant begins a moves by examining the pixel which its 
velocity vector points to.  The color of this pixel is the "tilecolor".
Then the ant uses lookup tables stored as its gene to use the tilecolor
and its present state to decide on i) its next state ii) its next
velocity vector iii) whether or not to color the cell the ant is now
leaving.
	I have used three vant/turmite modes of eating.  In the freeforall
mode, each trail cell of another colony that an ant sees counts for a
point.  In the cyclic mode, the colonies are thought of as a feeding
cycle, with, e.g., colony 1 trailcells counting as plus 2 points for the 
colony 2 ants, and the colony 3 trailcells counting as minus 1 points
for the colony 2 ants, and so on.  In the third mode, we also add 
neutral "wall" cells (which the ants bounce off of), and use these
walls to make mazes which have very valuable "food" cells of, say,
plus 4 points value near the center of the maze.  
	In every case, the ant colonies evolve internally and, more
interestingly, co-evolve to take advantage of each other.  An important
trick to make the vant/turmite worlds run nicely is to have the trails
NOT be permanent.  A program parameter sets each trailcell to disappear
after some number of steps, say 500.  A difficulty in having many 
possible directions is that, in order to distinguish, say, 128 directions,
an ant has to take radially large steps, meaning that its trail is
so spotty that other ants are unlikely to step on it.  This can be
corrected by replacing the "trailcell" with a "trailsegment" line
connecting successive positions --- this correction produces patterns
like frantic spirographs.
	I have also done some preliminary programs in which the ants can
see a certain distance (like Braitenberg vehicles); I have not yet
done anything with neural nets.  As I am associated with the ongoing
Autodesk cyberspace project, I am quite interested in putting ants into
3D space.  I think something like a Braitenberg or a flocking behaviour
will be needed in 3D --- because 3D lines cross each other so much more
rarely than 2D lines, the Turing approach will probably not work well
in 3D.
	I think one of the biggest problems at this point is FINDING
SOMETHING INTERESTING FOR THE ANTS TO DO.  The idea of having ants
compete against each other is a suggestive game-oriented application,
analagous to Core Wars.  But could the ants ever do something of
commercial interest?  Designing the circuits for chips and boards is
a possibil

e use.  But as Hiebeler has pointed out in earlier discussions,
there is special purpose hardware to to this.

From cellular-automata-request@Think.COM  Mon Feb  4 14:26:56 1991
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From: autodesk!air!rudy@fernwood.mpk.ca.us (Rudy Rucker)
Message-Id: <9102041839.AA01139@air.acad>
To: ca@Think.COM
Subject: RESEND Life Wars, Ants


The last message of mine was truncated during the send.  Disregard
that one, here is (God and Net willing) the correct text.
Chris Langton writes the following:

> I would be interested in seeing discussions of such CA-extensions in
> this group in addition to discussions of CA themselves. Much of what
> makes us interested in CA is retained in such systems: they are 
> bottom-up, spatially distributed collections of processes interacting 
> with one another. They are like CA in which the cells are free to move 
> about - or equivalently -in which the contents of cells are free to 
> move about if one insists on keeping the cells themselves fixed. They 
> may involve alterations to the basic CA paradigm, such as allowing 
> continuous representations of space or state instead of discrete ones,
> or allowing for arbitrarily powerful computing machines within each 
> "cell".                         

	Here is some information about experiments of this nature which 
I've been carrying out with so-called ants programs.  In an ants program,
you have a population of program objects which are displayed as moving
graphics icons.  In my experiments, an ant is a C++ object which has:
(x,y): position, (vx,vy): pixels-per-update velocity, s :a running score,
*move : a pointer to a function which computes the ant's next velocity
vector, *eat : a pointer to a function which changes the ant's 
score on the basis of what it encounters, and gene : an array of
"genetic" information that is used in computing the move function.
	Following a suggestion that was made at the A Life II conference,
I normally group my ants into colonies.  On the PC, it is practical to
have something like seven colonies of seven ants each.  At the end of 
each "antyear" (perhaps 2000 update cycles), the ants within each colony
compare their scores to their fellow colony members and are ranked.  The
worst two ants in a colony have their genes replaced by new gene
arrays derived from the genes of the best two ants.  Usually the 
third worst ant's genes are totally randomized as well.  This process
is carried out separately for each colony.  Very clear evolutionary
effects are seen.
	Intercolony evolutionary effects can be achieved by, for instance,
having the less successful colonies use a higher mutation rate.
	So far I have experimented with two general kinds of move
functions.  The simpler approach is based on Micahel  Palmiter's 
"Simulated Evolution" as described in K. Dewdney's recent anthology 
of columns, The Magic Machine (Freeman, 1990).  Here the ants move in
one of six planar directions.  At each update, each ant uses a randomizer
and a private table of probabilities to decide how many degrees to
turn.  If food is scarce, widely spread, and of positive weight, these
ants will evolve to turn rarely and travel in straight lines.  If the
food is concentrated in one region the ants will evolve to turn a lot,
and so on.
	A more interesting kind of antworld arises if we have our ants
move like 2-Dimensional Turing machines.  This paradigm was first 
explored by Langton in a CA setting, where he called them "vants."
Vants are also discussed in Dewdney's book, where he calls them
"turmites," and runs them as separate objects rather than as CAs.  In
my turmite/vant experiments, I allow the ants to move in up to 128
different directions.  Each ant has an internal state, (I've tried up
to 256 states, although very rich behavior already happens with 4
states).  Each colony of ants has a distincitve color of "trail" that
is lays down.  An ant begins a moves by examining the pixel which its 
velocity vector points to.  The color of this pixel is the "tilecolor".
Then the ant uses lookup tables stored as its gene to use the tilecolor
and its present state to decide on i) its next state ii) its next
velocity vector iii) whether or not to color the cell the ant is now
leaving.
	I have used three vant/turmite modes of eating.  In the freeforall
mode, each trail cell of another colony that an ant sees counts for a
point.  In the cyclic mode, the colonies are thought of as a feeding
cycle, with, e.g., colony 1 trailcells counting as plus 2 points for the 
colony 2 ants, and the colony 3 trailcells counting as minus 1 points
for the colony 2 ants, and so on.  In the third mode, we also add 
neutral "wall" cells (which the ants bounce off of), and use these
walls to make mazes which have very valuable "food" cells of, say,
plus 4 points value near the center of the maze.  
	In every case, the ant colonies evolve internally and, more
interestingly, co-evolve to take advantage of each other.  An important
trick to make the vant/turmite worlds run nicely is to have the trails
NOT be permanent.  A program parameter sets each trailcell to disappear
after some number of steps, say 500.  A difficulty in having many 
possible directions is that, in order to distinguish, say, 128 directions,
an ant has to take radially large steps, meaning that its trail is
so spotty that other ants are unlikely to step on it.  This can be
corrected by replacing the "trailcell" with a "trailsegment" line
connecting successive positions --- this correction produces patterns
like frantic spirographs.
	I have also done some preliminary programs in which the ants can
see a certain distance (like Braitenberg vehicles); I have not yet
done anything with neural nets.  As I am associated with the ongoing
Autodesk cyberspace project, I am quite interested in putting ants into
3D space.  I think something like a Braitenberg or a flocking behaviour
will be needed in 3D --- because 3D lines cross each other so much more
rarely than 2D lines, the Turing approach will probably not work well
in 3D.
	I think one of the biggest problems at this point is FINDING
SOMETHING INTERESTING FOR THE ANTS TO DO.  The idea of having ants
compete against each other is a suggestive game-oriented application,
analagous to Core Wars.  But could the ants ever do something of
commercial interest?  Designing the circuits for chips and boards is
a possibility that is sometimes mentioned, but, as I think Hiebeler
pointed out, there are already special purpose programs that do this
much more directly and efficiently.  One problem with using ant
programs is that evolution can be very SLOOOOW.  Chunking the ants
into colonies does provide, I think, a dramatic speedup in terms of
getting the best ant the fastest --- the reason being that the 
colonies are exploring alternate paths of evolution.  Even so,
after the initial thrill, watching ants evolve is maybe not much more
interesting than watching grass grow.
	I'd really appreciate some suggestions on the question of what
of commercial or recreational interest the ants can do.  My other
function at Autodesk besides developing applications for cyberspace
is to help write a (hopefully) continuing series of "Science" products
which enable the hobbyist or casual hacker to play with exciting
programs. The first product was our CA Lab, and the second was called 
James Gleick's Chaos: The Software.  I think I'd like to see something 
like ANTS! or "Artificial Life Lab" as a third product, but I'm just not
sure the program would have a broad enough appeal.  Suggestions?

OK, yes, that's the correct text.

From cellular-automata-request@Think.COM  Wed Feb  6 22:27:54 1991
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Date: 7 Feb 91 01:56:20 GMT
From: n8443916@unicorn.cc.wwu.edu (John Gossman)
Organization: Western Washington University, Bellingham
Subject: CA extensions
Message-Id: <1991Feb7.015620.17304@unicorn.cc.wwu.edu>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM


	Chris Langton requested other CA-like ideas people are
experimenting with, so here goes:

	I've been playing with a very simple A-life, mainly to
study Genetic algorithms for learning.  Basically the board is
a square, wrap-around lattice upon which random quantities of
food are scattered in chunks.  One square may have 10 units, another
3, another 0 with only about 1 in 3 having any food.

	The creatures consist of a stomach that is initially filled
with 8 (or so) units of food, a hunger that causes them to consume
one unit of food each turn, and a large gene.

	Basically, each creature each turn makes a binary number
based on how many cells in its 9-cell (including the one it is on)
have any food in them.  Thus there are 512 combinations (2^9) of
how food lies in its neighborhood.  The creature indexes its gene
with this number and finds a number telling it to move to one of
the 9 cells in its neighborhood.  If it lands on a cell with food,
it consumes one.  If it doesn't it consumes one from its stomach
until its stomach is empty, then it dies.

	The simulation drops 20 creatures onto the board randomly,
and keeps track of their average survival time, then breeds together
the 5 or 10 most successful ones in multiple ways.  Note that these
genes are initially COMPLETELY random, and new random creatures are
added in every generation.  
	Initially, with their random gene strategies, most die very
quickly (9-10 turns).  Within only 5 or 10 generations this improves
to 14-15 turns, and then continues slowly upwards.  I have noted that
the life-time seems to reach plateaus for 100s of generations, then
jump up suddenly, usually at the same key points (24 -> 30, 34 -> 42),
offering support for Gould's puncuated equilibrium theory of evolution.

	Finally, the creatures turned out to be smarter than I.  Given
20 creatures and the amount of food initially in their environment, I
estimated a maximum average survival time ~50 turns.  However, while
watching my experiments I found them surviving 60-65 turns after awhile.
After investigating my code, I discovered the creatures were exploiting
a "bug" in their universe.  If they moved off food, onto a blank square,
they neither consumed a unit on that square, nor in their stomachs.  Thus
by bouncing back and forth onto and off of a square with food, they can
survive 2 turns on one food unit!!

	Anyway, another very simple variation on A-life, using merely
an array of initially random numbers for "brains".  I was surprised by
the rapid pace of evolution.  My next try is for more interaction beteen
the creatures.


// *************************************************************** //
John Gossman
SoftSource      (206)676-0999 Phone
WWU Math Dept.
My employer stands behind all my opinions, except in public.
// ************************************************************** //

From cellular-automata-request@Think.COM  Thu Feb  7 08:27:39 1991
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Date: 7 Feb 91 08:24:16
From: hiebeler@Think.COM (Dave Hiebeler)
Organization: Thinking Machines Corporation
Subject: Re: CA extensions
Message-Id: <HIEBELER.91Feb7082416@custard.think.com>
Newsgroups: comp.theory.cell-automata
References: <1991Feb7.015620.17304@unicorn.cc.wwu.edu>
Sender: ca-request@Think.COM
To: ca@Think.COM

John Gossman (n8443916@unicorn.cc.wwu.edu) wrote:

> [description of simulation]
> I have noted that the life-time seems to reach plateaus for 100s of
> generations, then jump up suddenly, usually at the same key points (24
> -> 30, 34 -> 42), offering support for Gould's puncuated equilibrium
> theory of evolution.

  This offers support for a theory of punctuated equilibrium in a
CA-like system -- I think it is too simple to offer much evidence for
this phenomena as it may exist in the carbon-based biological world.
However, if many different kinds of models/simulations exhibit
behavior like this, then it could indicate that the phenomenon is
fairly common, and perhaps should be expected in biological systems as
well.


>	   Finally, the creatures turned out to be smarter than I.  Given
>   20 creatures and the amount of food initially in their environment, I
>   estimated a maximum average survival time ~50 turns.  However, while
>   watching my experiments I found them surviving 60-65 turns after awhile.
>   After investigating my code, I discovered the creatures were exploiting
>   a "bug" in their universe.

  This is actually fairly common, from what I've heard.  Many people
doing A-Life or CA-like simulations with evolution often find that the
systems learn to exploit bugs in the system.  I sometimes wonder if
humanity itself is nothing more than a bug in "The System". :-)

--
Dave Hiebeler                  | Internet: hiebeler@think.com
Thinking Machines Corporation  | Phone:  (617) 234-4070 (work)
245 First Street               | "Off we go, into the wilds you ponder."
Cambridge, MA 02142  USA       |

From cellular-automata-request@Think.COM  Thu Feb  7 09:16:29 1991
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Date: Thu, 7 Feb 91 07:16:03 MST
From: cgl@t13.lanl.gov (Chris Langton)
Message-Id: <9102071416.AA14396@t13.lanl.gov.>
To: ca@Think.COM
Subject: Re:  CA extensions

  John Gossman describes observing punctuated equilibria in the course of
the evolution of his CA system. 

  David Hiebeler correctly cautions that observing this phenomenon
in CA systems alone does not really constitute much support for PE
in biological evolution.

  However, this phenomenon is being seen in many different artificial
evolving systems, when people take care to record what happens along the
evolutionary path, instead of just noting that ``fitter-critters''
result at the end of the process.

  Indeed, many of the papers submitted for the proceedings of the most
recent workshop on Artificial Life note this phenomenon. Thus, is
appears that punctuated equilibrium behavior may well be ``generic''
for evolutionary processes.

These punctuation events are often accompanied by population crashes and 
``species'' crashes. This is important, because it suggests that extinction 
events on many different scales can occur due to the natural dynamics of 
the evolutionary process alone, without having to evoke catastrophes like
asteroid impacts. 

This is one of the better illustrations of the way in which Artificial 
Life can contribute to theoretical biology. By viewing evolutionary 
processes (and other biological processes) as dynamical systems, 
identifying what class of dynamical systems they are (if possible),
charting out the different regimes of dynamical behavior that such 
systems exhibit under different parameter settings and with different 
initial conditions, and even by altering the rules of the dynamical
system (for instance by allowing Lamarckian inheritance), we
can derive universal principles from an *ensemble* of examples, 
rather than trying to derive universals from the *single* examples 
that nature has given us of most biological processes.

  Viewing the evolutionary process as a dynamical system allows one 
to make an analogy between punctuated equilibrium dynamics and what 
is known as ``intermittency'' in dynamical systems. Intermittency is
a generic behavior for many dynamical systems near a phase-transition 
between periodic and chaotic behavior. Thus, the fact that evolutionary
processes exhibit dynamical intermittency suggests that evolution naturally
brings populations to some sort of phase-transition. This has a number
of interesting implications which I won't go into here, but suffice it
to say that the love affair between dynamical systems theory and biology
is only just beginning.

Cheers!

Chris Langton

Complex Systems Group
MS B213, Theoretical Division		Phone: 505-667-9471
Los Alamos National Laboratory		Email: cgl@t13.lanl.gov
Los Alamos, New Mexico, USA
87545





From cellular-automata-request@Think.COM  Thu Feb  7 19:27:50 1991
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Date: 7 Feb 91 21:35:03 GMT
From: brucec@phoebus.labs.tek.com (Bruce Cohen;;50-662;LP=A;)
Organization: Tektronix Inc.
Subject: Re: RESEND Life Wars, Ants
Message-Id: <BRUCEC.91Feb7133503@phoebus.labs.tek.com>
Newsgroups: comp.theory.cell-automata
References: <9102041839.AA01139@air.acad>
Sender: ca-request@Think.COM
To: ca@Think.COM

In article <9102041839.AA01139@air.acad> rudy@air.UUCP (Rudy Rucker)
writes:
...
>     I think one of the biggest problems at this point is FINDING
> SOMETHING INTERESTING FOR THE ANTS TO DO.  The idea of having ants
> compete against each other is a suggestive game-oriented application,
> analagous to Core Wars.  But could the ants ever do something of
> commercial interest?  Designing the circuits for chips and boards is
> a possibility that is sometimes mentioned, but, as I think Hiebeler
> pointed out, there are already special purpose programs that do this
> much more directly and efficiently.

Here's a half-baked suggestion: chemical synthesis.  One of the big
problems in synthesizing even simple organic compounds is that the yield
and overall reaction rate of the synthesis is dependent (usually in a
non-linear way) on the yields of the intermediate reactions, and often on
the yields of other reactions which inhibit the desired one.  Seems like
the kind of optimization problem which would yield (sorry!) to genetic
search.
--
------------------------------------------------------------------------
Speaker-to-managers, aka
Bruce Cohen, Computer Research Lab        email: brucec@tekchips.labs.tek.com
Tektronix Laboratories, Tektronix, Inc.                phone: (503)627-5241
M/S 50-662, P.O. Box 500, Beaverton, OR  97077

From cellular-automata-request@Think.COM  Thu Feb  7 23:40:49 1991
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From: cocteau <cocteau@brahms.udel.edu>
Message-Id: <9102080440.AA23144@brahms.udel.edu>
To: ca@Think.COM, hiebeler@Think.COM
Subject: Re: CA extensions

In all of our Alife simultions, we have found
strong evidence for punctuated evolution/ self organized
criticality all over the place.  Papers are forthcoming...
djp

From cellular-automata-request@Think.COM  Fri Feb  8 13:24:07 1991
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Date: 8 Feb 91 10:18:23 GMT
From: robina@castle.ed.ac.uk (Robin Allenson)
Organization: Edinburgh University Computing Service
Subject: summary of connectionism
Message-Id: <8362@castle.ed.ac.uk>
Newsgroups: comp.ai.neural-nets,comp.theory.cell-automata,bionet.molbio.evolution
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    I am trying to put together a short (15 min) talk on connectionism for some
people interested in AI, but not necessarily knowing a great deal about PDP.
Ideally, I want a short summary of the basic models, advantages, disadvantages,
and some applications. Can anyone suggest any books/articles that would do this
for me? If not, can anyone give email me what they think are the 'basics'.

    The NN-contest asked for a def'n  of NNs in a sentence. If anyone could
define connectionism in the above way in a paragraph, I'd be most interested.
If can you mail me, I'll mail the net a summary of the replies.

    Thanks,

    Robin Allenson

-----------------------------------------------------------------------------From cellular-automata-request@Think.COM  Fri Feb  8 15:20:43 1991
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Date: 8 Feb 91 20:06:51 GMT
From: pollack@dendrite.cis.ohio-state.edu (Jordan B Pollack)
Organization: Ohio State Computer Science
Subject: Re: CA extensions
Message-Id: <POLLACK.91Feb8150651@dendrite.cis.ohio-state.edu>
Newsgroups: comp.theory.cell-automata
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>  Indeed, many of the papers submitted for the proceedings of the most
>recent workshop on Artificial Life note this phenomenon. Thus, is
>appears that punctuated equilibrium behavior may well be ``generic''
>for evolutionary processes.

The principles underlying punctuated equilibria may also be generic
for other kinds of search and problem-solving. Certain kinds of
connectionist learning curves jump through discrete levels of
improvement. In my connectionist model of language induction to appear
in NIPS 3, a sequential parity learner undergoes a phase transition
which corresponds to the initial discovery of the xor "trick", which
is rapidly exploited (in some sort of arms race) by back propagation.
Human learning of mathematical concepts, gestalt recognition of
distorted objects, and insight problem-solving (the AHA phenomena)
also seem to be punctuated by phase transitions, where there no
progress until right before the problem is solved.  The idea of a
pre-adaptive change leading to a massive reorganization of population
elements seems to analogically apply.

>These punctuation events are often accompanied by population crashes and 
>``species'' crashes. This is important, because it suggests that extinction>events on many different scales can occur due to the natural dynamics of 
>the evolutionary process alone, without having to evoke catastrophes like
>asteroid impacts. 

Ive thought about that too, the idea that the asteroids and ET's
and continental breaks and are just truly random noise added to the
species bifurcation diagram. I even dallied with the idea of
collecting the best dating evidence on the time frame of species
introduction to see if it follows a classic period-double. The initial
result looked promising: the first 5/6 of the time, there were single
cellular creatures, then a long period of 2-cell creatures, then the
first explosion of multicellular types. We are in a period of
rapid species collapse due to humans (merging) with every other creature's
niche. I'm sure there is a nobel prize in here somewhere :)



--
Jordan Pollack                            Assistant Professor
CIS Dept/OSU                              Laboratory for AI Research
2036 Neil Ave                             Email: pollack@cis.ohio-state.edu
Columbus, OH 43210                        Fax/Phone: (614) 292-4890

From cellular-automata-request@Think.COM  Tue Feb 12 15:30:44 1991
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Date: 12 Feb 91 07:42:24 GMT
From: ro2m+@andrew.cmu.edu (Randy O'Reilly)
Organization: Carnegie Mellon, Pittsburgh, PA
Subject: Wacky Quantum Theory in CA
Message-Id: <UbhtlUC00WB_M3IJkh@andrew.cmu.edu>
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I have a wacky theory about quantum wave functions that I would be
interested in getting your opinions on.  It goes something like this:
What if all those probability functions obeying Schrodinger's equation
that Quantum Mechanics (QM) is based on *actually exist*, and further
that the mechanism which is creating these waves is a local,
continuous-valued CA whose mesh size (cell size) and rate of update
are somehow related to Plank's constant.  By continuous-valued CA, I
mean a CA system that has a real number in each cell, and some
function operating on the neighbors that updates the value of each
cell in such a way as to obey the various constraints imposed by
Schrodinger's EQ?  

Has anyone ever modeled wave behavior of any kind using such a setup?
It seems likely that constraints such as linearity and superposition
would significantly restrict the number of possible functions.  My
best hunch without delving into it is that something like an average
function would have the right qualities (eg. Cn = (Cn-1 + Cn+1) / 2).

I plan to attempt a mathematical analysis of a simple 1-dimensional
wave function and see what kinds of locally computed, real-valued
functions would do the trick, that is unless anyone out there knows
of, or has already done such a thing.  Also, if this is a trivial
exercise, please let me know ASAP (by email, ;-).  I have been
reluctant to sit down and figure out these complex wave functions, so
any pointers to relevant material would be appreciated...

-Randy
(ro2m+@andrew.cmu.edu)

From cellular-automata-request@Think.COM  Tue Feb 12 19:27:25 1991
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From: autodesk!air!rudy@fernwood.mpk.ca.us (Rudy Rucker)
Message-Id: <9102122351.AA01443@air.acad>
To: ca@Think.COM
Subject: wacky quantum CAs


Ed Fredkin used to talk about the possiblity of planck-constant sized
CAs running the universe.  There exist sets of notes on his talks,
I once got a set through a contact at the AI Lab at MIT.  

From cellular-automata-request@Think.COM  Wed Feb 13 04:29:08 1991
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Date: 13 Feb 91 07:53:30 GMT
From: kmc@netcom.COM (Kevin McCarty)
Organization: Netcom - Online Communication Services  UNIX System {408 241-9760 guest}
Subject: Re: Wacky Quantum Theory in CA
Message-Id: <23855@netcom.COM>
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Randy O'Reilly asks about wave phenomena in CA systems with continuous
state variables, but discrete space and time.  This kind of system was 
mentioned in a general framework in a recent article I saw that dealt
with the general phenomenon of pattern formation in the following
kinds of systems:

	Model			Space	Time	State
	-----			-----	----	-----
partial diff. eq'ns		C	C	C
iterated functional eqn's	C	D	C
oscillator chains		D	C	C
lattice dynamical systems	D	D	C
cellular automata		D	D	D

D = discrete
C = continuous

J. P. Crutchfield, K. Kaneko, "Phenomenology of Spatio-Temporal Chaos",
in "Directions in Chaos", Hao Bai-lin, ed., World Scientific, 1987.

The lattice dynamical systems are what numerical analysts really study
when they discretize P.D.E.'s for computation.  Autonomous,
non-quiescent behavior of such systems is a botheration to numerical
analysts though, and they strive to avoid it by quantizing
'appropriately'.  If you're looking for self-organizing wave phenomena,
why then begin with a numerical analysis text and learn about 'numerical
instability'.  The above-referenced article looks at the topic from a
fresh perspective though, and presents an interesting catalog of
lattice dynamical system phenomena.

From cellular-automata-request@Think.COM  Wed Feb 13 10:31:01 1991
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Date: 12 Feb 91 07:42:24 GMT
From: ro2m+@andrew.cmu.edu (Randy O'Reilly)
Organization: Carnegie Mellon, Pittsburgh, PA
Subject: Wacky Quantum Theory in CA
Message-Id: <UbhtlUC00WB_M3IJkh@andrew.cmu.edu>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM


I have a wacky theory about quantum wave functions that I would be
interested in getting your opinions on.  It goes something like this:
What if all those probability functions obeying Schrodinger's equation
that Quantum Mechanics (QM) is based on *actually exist*, and further
that the mechanism which is creating these waves is a local,
continuous-valued CA whose mesh size (cell size) and rate of update
are somehow related to Plank's constant.  By continuous-valued CA, I
mean a CA system that has a real number in each cell, and some
function operating on the neighbors that updates the value of each
cell in such a way as to obey the various constraints imposed by
Schrodinger's EQ?  

Has anyone ever modeled wave behavior of any kind using such a setup?
It seems likely that constraints such as linearity and superposition
would significantly restrict the number of possible functions.  My
best hunch without delving into it is that something like an average
function would have the right qualities (eg. Cn = (Cn-1 + Cn+1) / 2).

I plan to attempt a mathematical analysis of a simple 1-dimensional
wave function and see what kinds of locally computed, real-valued
functions would do the trick, that is unless anyone out there knows
of, or has already done such a thing.  Also, if this is a trivial
exercise, please let me know ASAP (by email, ;-).  I have been
reluctant to sit down and figure out these complex wave functions, so
any pointers to relevant material would be appreciated...

-Randy
(ro2m+@andrew.cmu.edu)

From cellular-automata-request@Think.COM  Thu Feb 14 10:26:30 1991
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Date: 14 Feb 91 15:27:29 GMT
From: hiebeler@Think.COM (Dave Hiebeler)
Organization: Thinking Machines Corporation
Subject: Postdoc in lattice gas
Message-Id: <HIEBELER.91Feb14092729@custard.think.com>
Newsgroups: comp.theory.cell-automata
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[The following is being posted for someone else; please do not respond
directly to me.  -Dave]


	Postdoctoral researchers sought for developing lattice gas models
on a connection machine at the Naval Research Laboratory.  NRL is developing
a lattice gas model for wave propagation, specifically for ocean acoustics.
A preliminary 2-d model has simulated reflection, transmission and scattering
processes accurately.  A 3-d model is under development.  The work is 
unclassified and publication is encouraged.  Much of the development is being
done jointly with the Center for Nonlinear Studies at Los Alamos.  Postdoctoral
Fellowships supported by the Office of Naval Technology are available to US
citizens who have completed their doctorates since 1986 or are in the process
of finishing their work currently.  

	For information on the fellowship write:
	ONT Postdoctoral Program
	Projects Office
	ASEE
	Eleven Dupont Circle
	Suite 200
	Washington, DC  20036
Deadlines for application are:
	1 April, 1 July or 1 October

For more information on the technical program contact:
	Dr. Susan K. Numrich, Code 5150
	Naval Research Laboratory
	Washington, DC 20375-5000
		(202) 404-7345
	numrich@cmsun.nrl.navy.mil

--
Dave Hiebeler                  | Internet: hiebeler@think.com
Thinking Machines Corporation  | Phone:  (617) 234-4070 (work)
245 First Street               |
Cambridge, MA 02142  USA       |

From cellular-automata-request@Think.COM  Mon Feb 18 02:59:34 1991
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Date: 17 Feb 91 04:07:24 GMT
From: burns@latcs1.oz.au (Jonathan Burns)
Organization: Comp Sci, La Trobe Uni, Australia
Subject: Re: RESEND Life Wars, Ants
Message-Id: <9543@latcs1.oz.au>
Newsgroups: comp.theory.cell-automata
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Thanks to: brucec@phoebus.labs.tek.com (Bruce Cohen;;50-662;LP=A;)
in <BRUCEC.91Feb7133503@phoebus.labs.tek.com>

In article <9102041839.AA01139@air.acad> rudy@air.UUCP (Rudy Rucker)
writes:
...
>     I think one of the biggest problems at this point is FINDING
> SOMETHING INTERESTING FOR THE ANTS TO DO.  The idea of having ants
> compete against each other is a suggestive game-oriented application,
> analagous to Core Wars.  But could the ants ever do something of
> commercial interest?  Designing the circuits for chips and boards is
> a possibility that is sometimes mentioned, but, as I think Hiebeler
> pointed out, there are already special purpose programs that do this
> much more directly and efficiently.

My impression is that ants would be good at tesselation problems. In
particular, a memory manager, say for virtual storage, could be built
on the basis of static objects (cells) which represent pages in
virtual and real address-space, plus mobile objects (ants) which run
around linking pages together, promoting virtual pages to real and
copying reals back to virtual.

The question is: among VM algorithms, are there already cheap ones that
get 80% usage or so from real storage? Is it worth investing in CA
mechanisms to try and claim another 10%?

Answer: maybe so. Inituition says that a bottleneck develops when 
storage is large, but is managed by a uniprocessor. So, run multiple
MMU's (memory management units) in parallel. But now you have to
arbitrate communications between the MMUs. So, set them up with a
regular neighbourhood topology, and give each a simple set of state
rules. Voila, CA.

Then, for instance, write a new instruction set for a VLIW machine
in emulation. Run a test suite on it repeatedly. Let the ants find
their own rules for locally optimum performance. Burn the rules in.

A similar, maybe even more suitable application is disk space management
for file systems and databases.

A pleasant aspect is that cached storage is a modular part of any
system. Build a cache with CA smarts, and it doesn't entail any change
in CPU architecture.


~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Jonathan Burns        | Clashing for the warrior, whose strength is not to fight
burns@latcs1.lat.oz.au| Clashing for the refugee, on the unarmed road of flight
Computer Science Dept | And for each and every underdog soldier in the night
La Trobe University   | We gazed upon the chimes of freedom flashing    -Dylan
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

From cellular-automata-request@Think.COM  Mon Feb 18 03:58:16 1991
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Date: 17 Feb 91 15:14:31 GMT
From: marek@iuvax.cs.indiana.edu (Marek W Lugowski)
Organization: Computer Science, Indiana University, Bloomington.
Subject: Missing the anthill for the ants? (was Re: RESEND Life Wars, Ants)
Message-Id: <1991Feb17.101444.17544@news.cs.indiana.edu>
Newsgroups: comp.theory.cell-automata
References: <9543@latcs1.oz.au>
Sender: ca-request@Think.COM
To: ca@Think.COM

All this talk of ants and my recent experiments with Computational Metabolism
(C. Langton's _Artificial Life_, pp. 343-368), a tiling in motion, make me
wonder about the utility of looking at ants through the prism of their final,
or evolved, states.  After all, these states are only fixed attractors with
respect to the local conditions and the chaotic space.  How much is there
of interest, computationally, in such attractors?  What can you learn from
reaching them about any computation of interest, other than discrimination a
la pattern recognition/categorization in the way of Widrow-Hoff or a steepest
descent algorithm as found in simplest neural nets?  That's boring...

What I think is of interest is the path taken through the chaotic
space.  You may think of it as an informationally sensitive carrier
wave, a la FM-modulation.  There is enough richness specified in this
path to encode a lot more than simple partition of the input space in
a static recognition problem.  For this you don't even need evolution
to get started: I found out that for my tiles, which are no ants
believe you me :), for different initial arrangements, under a
particularly nasty set of rules that has the tiles leaping out of
their little selves to wrap each species (color) around each other
(you have to see the pictures...), I get stunningly different and
beautifully chaotic paths to ...you guessed it, an attractor, one
that, of course, I suspected anyway, since my rules don't change and I
designed them for a square gworld and ran on a torus one.  Now, if I
could only learn how to modulate the path to effect an effective
computation = controlled chaos...

In summary, worry about paths in chaotic space and modulating them (and
representing the process as a grammar, unfolding) instead of computing
arrivals.

Any thoughts, disagreements?

				-- Marek

cc'ed to alife@iuvax.cs.indiana.edu, *the* mailing list :)
(alife-request@iuvax for additions)

From cellular-automata-request@Think.COM  Mon Feb 18 05:58:05 1991
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Date: 18 Feb 91 02:52:23 GMT
From: tomh.bbs@shark.cs.fau.edu (Tom Holroyd)
Organization: Florida Atlantic University
Subject: Something for the ants to do
Message-Id: <16mJX2w163w@shark.cs.fau.edu>
Newsgroups: comp.theory.cell-automata
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If we want the ants to create some higher level organization,
they must cooperate with one another, as well as compete against
constraints in the environment and rival ant species.

Real ants form living bridges to cross large (to them) obstacles;
why not try to evolve some ants that cross simulated barriers?

Bees dance to inform other bees about food sources; how about
some alife bees that communicate similar info to other bees of
the same family?  Note that several families of bees need to
compete against each other to find the best communication
strategy.

I've seen too many "bugs" that evolve the ability to find "food"
efficiently.  Let's get out of the hunter-gatherer stage and try
to evolve some bugs that FARM.  Even one bug that raises a crop
and defends territory would count, since then the bug is cooperating
with the food species, leading to symbiosis.

Don't worry so much about deciding what the ants should be doing
at this stage; get them to cooperate effectively and new high-level
behaviors based on simple sub-behaviors should emerge almost by
themselves.

tomh@bambi.ccs.fau.edu
Tom Holroyd
Florida Atlantic University
Center for Complex Systems
"An anthill is a queen's way of making another queen."

From cellular-automata-request@Think.COM  Mon Feb 18 06:58:22 1991
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Date: 18 Feb 91 05:11:11 GMT
From: marek@iuvax.cs.indiana.edu (Marek W Lugowski)
Organization: Computer Science, Indiana University, Bloomington.
Subject: Re: Something for the ants to do
Message-Id: <1991Feb18.001127.16317@news.cs.indiana.edu>
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In article <16mJX2w163w@shark.cs.fau.edu> tomh.bbs@shark.cs.fau.edu
(Tom Holroyd) writes:
>If we want the ants to create some higher level organization,
>they must cooperate with one another, as well as compete against
>constraints in the environment and rival ant species.
....
>
>Don't worry so much about deciding what the ants should be doing
>at this stage; get them to cooperate effectively and new high-level
>behaviors based on simple sub-behaviors should emerge almost by
>themselves.
>
>tomh@bambi.ccs.fau.edu
>Tom Holroyd
>Florida Atlantic University
>Center for Complex Systems
>"An anthill is a queen's way of making another queen."

I think those two statements are incompatible.  While I agree with the
former, I can't quite see how ecosystemic constraints reduce to
arbitrary sub-behaviors on which something meaningful is based.  I would
say:  Worry very much about what the ants ought to be doing (i.e., what
path in chaotic space they are to be computing) and by proper design
at first and natural selection later, get them to cooperate effectively.

I don't buy into this "should emerge almost by themselves."  That's just
alife propaganda that we should be careful not to get zapped with.  In
real life, the ecosystem and the pressures from without as well as from
within form a complex slippage of constraints, none of which is arbitrary.
To compute with ants ex nihilo is artificial intelligence pure and simple:
you are just defining arbitrary symbols and shoving them around, with a
bit of optimization thrown in for good measure.  If so, anthill-climbing
is not too far from hill-climbing (search) period.

What we should be doing is trying to replicate a microcosm and computing
with it.  This will take nontrivial amount of design and tweaking, because
we will be making up for the absence of natural constraints.

I share Tom's call for better ants, but only via a better antworld.

				-- Marek

cc: alife@iuvax.cs.indiana.edu (alife-request for additions)

From cellular-automata-request@Think.COM  Tue Feb 19 00:04:47 1991
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Date: 18 Feb 91 13:30:28 GMT
From: tomh.bbs@shark.cs.fau.edu (Tom Holroyd)
Organization: Florida Atlantic University
Subject: Re: Something for the ants to do
Message-Id: <HPgkX1w163w@shark.cs.fau.edu>
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marek@iuvax.cs.indiana.edu (Marek W Lugowski) writes:
> I don't buy into this "should emerge almost by themselves."  That's just
> alife propaganda that we should be careful not to get zapped with.  In

OK, sorry for the somewhat un-scientific statement.  In the real world,
interesting behavior DID emerge by itself, but perhaps only because
the environment itself was already complex.  As Marek says, better
ants via better antworlds.  Additionally, directed evolution can be
a lot faster than waiting for it to happen "by itself".

Cooperation between ants at least requires that the ants be able to
communicate with each other.  (If all the ants are turning to the left
because their programs say turn left, I don't call that cooperation.)
A uniform dynamical system with positive feedback can undergo a
symmetry breaking, where small random fluctuations are amplified
into some non-uniform structure.  What I'm hoping is that an initially
uniform scattering of ants which positively reinforce each other's
behavior could spontaneously generate some structure (a higher level
of organization than just one ant).  Selection would then operate
on the higher level structure.

The point is that if I want to have the ants cross a river, I
don't want to program each ant with "bridge building and river
crossing" behaviors; rather, I would give them the ability to
communicate and cooperate with each other, and let them self-
organize a behavior which, if it resulted in the ants crossing
the river, would be selected for.

Tom Holroyd
Florida Atlantic University
Center for Complex Systems
tomh@bambi.ccs.fau.edu

> cc: alife@iuvax.cs.indiana.edu (alife-request for additions)

From cellular-automata-request@Think.COM  Tue Feb 19 04:59:22 1991
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Date: 18 Feb 91 19:57:18 GMT
From: aboulang@bbn.com (Albert Boulanger)
Organization: BBN, Cambridge MA
Subject: Re: Missing the anthill for the ants? (was Re: RESEND Life Wars, Ants)
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In article <1991Feb17.101444.17544@news.cs.indiana.edu> marek@iuvax.cs.indiana.edu
(Marek W Lugowski) writes:

   What I think is of interest is the path taken through the chaotic
   space.  You may think of it as an informationally sensitive carrier
   wave, a la FM-modulation.  There is enough richness specified in this
   path to encode a lot more than simple partition of the input space in
   a static recognition problem.  For this you don't even need evolution
   to get started: I found out that for my tiles, which are no ants
   believe you me :), for different initial arrangements, under a
   particularly nasty set of rules that has the tiles leaping out of
   their little selves to wrap each species (color) around each other
   (you have to see the pictures...), I get stunningly different and
   beautifully chaotic paths to ...you guessed it, an attractor, one
   that, of course, I suspected anyway, since my rules don't change and I
   designed them for a square gworld and ran on a torus one.  Now, if I
   could only learn how to modulate the path to effect an effective
   computation = controlled chaos...

   Any thoughts, disagreements?


Yes, two thoughts:

*****************************1************************************
Trajectories instead of basins for computation:

Asymmetric recurrent (Hopfield) neural nets have interesting (and
trainable) trajectories.

"Temporal Associations in Asymmetric Neural Networks", H Sompolinsky
and I.  Kanter, Phys Rev Lettr, Vol 57, No 22, 2861-2864

"Statistical Mechanics of Neural Networks", H. Sompolinsky, Physics
Today, Dec. 1988, 70-80

"Hebbian Learning Reconsidered: Representation of Static and Dynamic
Objects in Associative Neural Nets", A. Hertz, B. Sulzer, R. Kuhn,
and J.L. Hemmen, Biol. Cybern., Vol 60, 1989, 457-467

Freeman and others have been proposing an the use of periodic
attractors for associative memory:

"Associative Memory in a Simple Model of Oscillating Cortex" Bill
Baird, NIPS 2 Proceedings, D. Touretsky Ed, Morgan Kaufman.

Backprop has been modified to work with hidden-layer networks with
feedback connections and have the ability to learn phase-space
trajectories. Many people have worked on this one:

"Learning State Space Trajectories in Recurrent Neural Networks, Barak
Pearlmutter, CMU Computer Science Report CMU-CS-88-191, Dec. 31, 1988

"Generalization of Back-Propagation to Recurrent Neural Networks"
Fernando Pineda, Phys Rev Lettr, Vol 59, No 19, 2229-2232

Optical feedback with 4-wave mixing using photorefractive
materials have interesting associative cycling behavior.

*******************************2*********************************
Chaos and computation

Actually there are times that one wishes to use the ergodic properties
of chaos in computation. This is a way of doing search. There is an
annealing-like algorithm that makes use of this:


"Chaotic Optimization and the Construction of Fractals: Solution of an
Inverse Problem"
Giorgio Mantica & Alan Sloan
Complex Systems 3(1989), 37-62


Finally, here is some recent work by Crutchfield and Young in analyzing the
pattern generation properties (using grammars) of system on the verge
of chaos:

"Computation at the Onset of Chaos",  James Crutchfield and  Karl
Young, appearing in "Complexity, Entropy, and the Physics of
Information", W. Zurek, ed., Addison-Wesley, 1989/



Harnessing chaos,
Albert Boulanger
aboulanger@bbn.com

From cellular-automata-request@Think.COM  Tue Feb 19 08:58:14 1991
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Date: 19 Feb 91 12:26:48 GMT
From: rcstack@rw5.urc.tue.nl (Studenten Vereniging Stack)
Subject: Turing machine in Life: request for repost
Message-Id: <rcstack.666966408@rw5.urc.tue.nl>
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Some time ago P.Callahan posted a series of articles in which he sought
a proof of Life's universality. He did this by constructing a turing
machine, because he thought that this would be simpler than a complete 
computer. (Which Berlekamp, Conway and Guy constructed in 'Winning ways')

Somehow I lost the articles. I would like to read them again (and this time
keep them) because now I have also read 'Winning ways'.
I believe that the Life computer presented there (or rather the elements to
build one) will not work. I hope Callahan's TM will.

So if anyone could repost them, or mail them to angelo@gem.stack.urc.tue.nl
I'd be very thankful.

Angelo Wentzler
-- 
=============================================================================
Email: Internet: rcstack@urc.tue.nl              Bitnet: rcstack1@heitue5
Computer Association STACK, Computing Centre RC 1.82,
Eindhoven University of Technology, POBox 513, 5600 MB Eindhoven, Holland.

From cellular-automata-request@Think.COM  Tue Feb 19 08:58:40 1991
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Date: 19 Feb 91 12:13:07 GMT
From: xanthian@zorch.SF-Bay.ORG (Kent Paul Dolan)
Organization: SF-Bay Public-Access Unix
Subject: Re: Something for the ants to do
Message-Id: <1991Feb19.121307.29165@zorch.SF-Bay.ORG>
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A couple of things still seem to be lacking to have anthills that do
interesting things:

1) Much bigger anthills; it is a bit much to expect behavior networks
   typical of colonies of thousands of individuals to be emulated by
   colonies of seven individuals.

2) Extra-genetic differentiation of individuals within a colony: at least
   bees, and I think ants also, raise up grossly different individuals from
   similarly genetically endowed eggs by particular feeding schedules/choices,
   and the colony is based on separation of tasks to suitable individuals.
   Thus, an individual ant's genetic complement should represent a variety
   of possible mature individuals.

3) Which brings up the need to emulate nurturing behavior.

4) And also cooperative food gathering; bee and ant colonies contain some
   individuals who function as the colony's liver or gut; create food that
   can only be digested to utility for other ants by ants who can't gather
   it, and too big for an individual ant to drag home.

5) And allow for this very low level specialization: locomotor, digestive,
   reproductive, etc. with tradeoffs and improved efficiency in the area of
   specialization.

6) Folks who haven't, should read Douglas Hofstadter's Goedel, Escher, Bach,
   An Eternal Golden Braid for motivational material on ant colony
   functioning, especially when trying to envision things an ant colony
   could do.

Kent, the man from xanth.
<xanthian@Zorch.SF-Bay.ORG> <xanthian@well.sf.ca.us>

From cellular-automata-request@Think.COM  Tue Feb 19 10:25:31 1991
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Date: Tue, 19 Feb 91 08:25:03 MST
From: cgl@t13.Lanl.GOV (Chris Langton)
Message-Id: <9102191525.AA08177@t13.lanl.gov>
To: ca@Think.COM
Subject: Berelekamp/Conway proof...


angelo@gem.stack.urc.tue.nl writes:

>  .....because now I have also read 'Winning ways'.
>  I believe that the Life computer presented there (or rather the 
>  elements to build one) will not work. I hope Callahan's TM will.

  Can you expand on your doubts about this proof? 
  
  I have implemented many of the components, and they seem to work
  as advertised...
  
  Where do you think the Life computer presented in Winning Ways 
  breaks down?
  
   Cheers!

   Chris Langton

   Complex Systems Group
   MS B213, Theoretical Division	Phone: (505) 667-9471
   Los Alamos National Laboratory	Email: cgl@t13.lanl.gov
   Los Alamos, New Mexico, USA		FAX:   (505) 665-3003
   87545

<<<<<<<<<<<<<<<<<<<...Its...Its...Its Alive!...>>>>>>>>>>>>>>>>>>>

 

  

From cellular-automata-request@Think.COM  Wed Feb 20 05:58:30 1991
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Date: 20 Feb 91 10:20:57 GMT
From: jhaataja@finsun.csc.fi (Juha Haataja)
Organization: Centre for Scientific Computing, Finland
Subject: Workshop on Cellular Automata, April 17-18, 1991; CALL FOR PAPERS
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                     FINAL CALL FOR PAPERS

                 Workshop on Cellular Automata 
                       April 17-18, 1991
  
                Centre for Scientific Computing 
                       Helsinki, Finland


1.   BACKGROUND

Cellular automata are spatially and temporally discrete  dynamical  systems 
consisting  of identical cells arranged in a lattice.  The cells assume one 
of  a finite  number  of values  and are  updated according to a  spatially 
homogeneous local rule. These systems exhibit the prototypes of interactive 
dynamics.  Due to this  rich spectrum  of behavior  they have  applications 
in a number of areas of science and engineering.

A workshop on  cellular  automata  will  be  arranged  at  the  Centre  for
Scientific  Computing  (CSC)  in  Helsinki,  Finland, on April 17-18, 1991.
Papers presenting new theoretical results, or experiences of using cellular
automata  as modeling  tools,  are sought.  Point  of view  can be  general 
mathematics (for example dynamical systems theory),  computational science, 
physics, or other natural sciences.


2.   SPEAKERS

The main speakers are:

  Per Bak, Department of Physics, Brookhaven National Laboratory, USA
  "Self-Organized Criticality"

  Bruce M. Boghosian, Thinking Machines Corporation, Cambridge,
  Massachusetts, USA
  "A Survey of Lattice Gas and Lattice Boltzmann Methods for Hydrodynamics"

  David Griffeath, University of Wisconsin, Madison, USA
  "Excitable Cellular Automata"

  Clifford Pickover, IBM T.J. Watson Research Center, USA
  "Visualization of Complex Phenomena"

These presentations will be organized as two 45 minute sessions each.


3.   SUBMISSIONS

We are searching for short, 15-30 minute presentations. These  can  include
video,  slide  or  computer  demonstrations.  We  try  to  include  as many
presentations as possible, but if this  can't  be  arranged,  some  may  be
included  as  posters.  The  presentations  should  be aimed to people with
general scientific  background,  and  too  much  specialization  should  be
avoided.
  

4.   REGISTRATION

The registrations and submissions should be sent to the following address:

  Paula Maki-Valkkila
  VTKK/TLP
  P.O. Box 40
  SF-02101 Espoo
  Finland

E-mail: maki@csc.fi. Phone: +358 0 457 2718. Telefax: +358 0 457 2302.

The organizers can make hotel reservations for participants, when needed.
The walking distance to hotel Dipoli is 10 minutes.  The cost of a single
room is approx. 450 FIM for one night (ca. 120 USD).

Submissions should include the following information:

  Title of presentation
  Abstract (not much more than one page)
  Possible bibliography
  Duration of presentation (15-30 minutes)
  Special equipment needed (slide, video equipment etc.)

The deadline for registration to the workshop is April 8,  1991.  Abstracts 
of  submitted  papers  must be received  before March 1,  1991.  Authors of 
submitted papers will be notified of acceptance or rejection.  

The proceedings of the workshop will be published in the CSC Report Series,
and the deadline for the final papers will be announced later.


5.   ORGANIZERS

The organizing committee for the workshop consists of the following people:

  Prof. Risto Nieminen, CSC
  Dr. Kari Eloranta, Helsinki University of Technology
  Mr. Olli-Pekka Piirila, Helsinki University of Technology
  Dr. Jarkko Kari, University of Turku
  Mr. Esko Jarvinen, CSC
  Mr. Juha Haataja, CSC


6.   ARRANGEMENTS

There is no registration fee for academic participants; for others, the fee
is $100.

For additional information, contact Juha Haataja (jhaataja@finsun.csc.fi
or JHAATAJA at FINFUN) at the Centre for Scientific Computing.

From cellular-automata-request@Think.COM  Wed Feb 20 09:58:43 1991
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Date: 20 Feb 91 11:27:48 GMT
From: clarg@sparcst1.essex.ac.uk (Clarke G)
Organization: University of Essex, Colchester, UK
Subject: request for information
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Subject: Information
The discussion of ants, hills, etc has led to my reaching critical mass
regarding my interests in doing something in this field. I have been
listening to the group for sometime now and realise that my listening has
been highly selective since I don't_remember/haven't_recorded details of either
the significant texts or the significant software. If someone could provide the
details I would be grateful. The software should be publicly accessible and
as cheap as possible, preferably free. If the books tell you how to write it
then OK. The sort of hardware I have available is Sun 3-50, 3-60, Sparc, Apollo
DN3000, IBM PC-AT.
U.K. listeners may have seen part of a recent TV series called "The Trials of
Life", one part of which looked at social behaviour and in particular the
social behaviour of dwarf mongeese, mole rats and leaf cutter ants. There
was enough detail there, I suggest, to provide the basis for an artificial
life like simulation. Given David Attenborough's popularity I expect the
series will be sold to U.S. television.
My interests are in modelling social organisation (human) but it seems that
initially the tractable end of that is likely to reside in biological social
organisation or artificial life - organism AND environment.

----------------------------------------------------------------------
Graham Clarke, Computer Technical Officer, Dept. of Computer Science,
University of Essex, Wivenhoe Park, Colchester CO4 3SQ, Essex, England
Email: clarg@uk.ac.essex OR essex.ac.uk       Telephone:+44 0206 87234
----------------------------------------------------------------------

From cellular-automata-request@Think.COM  Thu Feb 21 01:47:19 1991
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From: autodesk!air!rudy@fernwood.mpk.ca.us (Rudy Rucker)
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To: ca@Think.COM
Subject: what KIND of free ant software


The program is for DOS disks to run on a PC with 
graphics.  Tell me what kind of disk you need.
Only written requests will be reliably answered.

From cellular-automata-request@Think.COM  Thu Feb 21 01:47:57 1991
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From: autodesk!air!rudy@fernwood.mpk.ca.us (Rudy Rucker)
Message-Id: <9102210622.AA04404@air.acad>
To: ca@Think.COM
Subject: free ant software


People keep asking for public domain ant software.

By way of casting break on the waters, I am going to freely
distibute the source and excecutable for my best ant
program, as described in previous mail.  The program is
called ant21.  Write me and I'll send you the executable,
(the source is held back for now), send your mailing
address to 

Rudy Rucker
ANTS
Autodesk, Inc.
2320 Marinship Way
Sausalito, CA 94965

Absoutely Free

From cellular-automata-request@Think.COM  Fri Feb 22 15:30:04 1991
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Date: Fri, 22 Feb 1991 15:25-0500
From: Allan C. Wechsler <ACW@YUKON.SCRC.Symbolics.COM>
Subject: source for Gosper's Hashlife
To: fontenot@rice.edu, ca@Think.COM
Cc: RWG@YUKON.SCRC.Symbolics.COM
In-Reply-To: <1991Jan28.203508.27886@rice.edu>
Message-Id: <19910222202533.9.ACW@WHIMBREL.SCRC.Symbolics.COM>

    Date: Mon, 28 Jan 1991 15:35 EST
    From: fontenot@rice.edu (Dwayne Jacques Fontenot)

    Hello,

    Does anyone know where I can get some source or a pseudo-code algorithm
    for Bill Gosper's "Hashlife"?

    The information I have says that the hashlife algorithm was designed in 1982
    and that it uses self-referential hash tables to store lookup patterns for
    John Conway's game of life. The algorithm is somewhat adaptive in that it
    "learns" which patterns to store and works up from relatively small patterns
    (4 x 4) to arbitrarily large ones.

    As you might deduce from the above, the algorithm starts out slowly and then
    accelerates logarithmically. I deduce that it uses memory in the same way ;-)

    The algorithm has the intriguing property of storing, in the hash table, all
    the information to recreate the life universe at any time in its history.
    Gosper was described as running backwards and forwards in time to see how
    interesting forms were produced.

    The description I saw (in the book, Mind Children) was not complete enough
    (in my opinion, anyway) for me to implement the alogorithm.
    I would like to implement this algorithm, but I believe I need a better
    description than was given in the book. Source code of any kind would be
    even better...

    Thank you for your time,

    Dwayne Fontenot
    fontenot@uncle-bens.rice.edu

I am forwarding your message to Gosper in case he hasn't seen the
request.

From cellular-automata-request@Think.COM  Fri Feb 22 15:43:14 1991
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Subject: Item for Distribution

**************************************************************************


                        *****************
                        *               *
                        *  A I S B 9 1  *
                        *               *
                        *****************
 
                     UNIVERSITY OF LEEDS, UK

                       16 - 19 APRIL 1991

                   TUTORIAL PROGRAMME 16 APRIL

                 TECHNICAL PROGRAMME 17-19 APRIL
                        with sessions on:
                  * Distributed Intelligent Agents
                  * Situatedness and Emergence in Autonomous Agents
                  * New Modes of Reasoning
                  * The Knowledge Level Perspective
                  * Theorem Proving
                  * Machine Learning

      Programmes and registration forms are now available from:
                  Barbara Smith
                  AISB91 Local Organizer
                  School of Computer Sudies
                  University of Leeds
                  Leeds LS2 9JT, UK

                  email: aisb91@ai.leeds.ac.uk

***************************************************************************

From cellular-automata-request@Think.COM  Sat Feb 23 04:59:25 1991
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Date: 22 Feb 91 20:13:01 GMT
From: fangyang@alhena.usc.edu (Fang Yang)
Organization: University of Southern California, Los Angeles, CA
Subject: Re: Workshop on Cellular Automata, April 17-18, 1991; CALL FOR PAPERS
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Newsgroups: comp.theory.cell-automata,comp.theory.self-org-sys
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test

From cellular-automata-request@Think.COM  Sun Feb 24 04:01:57 1991
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Date: 23 Feb 91 08:35:09 GMT
From: shiva@well.sf.ca.us (Kenneth Porter)
Subject: CAM 6 Engineer Announces Presence
Message-Id: <23300@well.sf.ca.us>
Newsgroups: comp.theory.cell-automata
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Just wanted everyone here to know that one of the co-developers
of the CAM-6 coprocessor is reading your newsgroup and I'm
happy to field questions or just chat.  Alas, I stopped working
at the company that made the CAM-6 a couple of years back, so I
no longer have access to the hardware, but I have a pretty good
memory :-).  Do many of you use a CAM-6?  I know that they were
hard to get back then.

Ken (shiva@well.sf.ca.us)

From cellular-automata-request@Think.COM  Mon Feb 25 15:59:46 1991
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Date: 25 Feb 91 20:28:28 GMT
From: scott@ferrari.LABS.TEK.COM (Scott Huddleston)
Organization: Computer Research Laboratory, Tektronix, Inc., Beaverton OR
Subject: Re: Berelekamp/Conway proof...
Message-Id: <7824@tekchips.LABS.TEK.COM>
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In article <9102191525.AA08177@t13.lanl.gov> cgl@t13.Lanl.GOV (Chris Langton) writes:
>angelo@gem.stack.urc.tue.nl writes:
>>  .....because now I have also read 'Winning ways'.
>>  I believe that the Life computer presented there (or rather the 
>>  elements to build one) will not work. I hope Callahan's TM will.
>
>  Can you expand on your doubts about this proof? 
>  
>  I have implemented many of the components, and they seem to work
>  as advertised...
>  
>  Where do you think the Life computer presented in Winning Ways 
>  breaks down?

I'm not angelo@gem.stack.urc.tue.nl, but I have some doubts about the
Berlekamp/Conway proof.  Here they are.

I question their constructions that require creating glider guns
at arbitrarily large distances away from a starting configuration.
To transport the gliders used as basic components to their destination,
their construction sends the gliders up between 2 parallel streams
in a kickback reaction.  I have a serious doubt and a minor qualm.

1. Look at the arrival timing constraints on the gliders used to
build a glider gun.  Most can arrive arbitrarily far apart in time,
which will work fine with the Berlekamp/Conway transport contruction.
But one pair must arrive at a precisely synchronized time, a few ticks
behind its predecessor.  How can a Berlekamp/Conway 2-stream kickback
transport accomplish this?
(Comment:  The "standard" (i.e. oft-repeated) construction of a glider
gun from gliders uses 13 gliders.  But 12 suffice (an exercise for the
reader).  My question applies to both constructions.)

2. (minor qualm) The Berlekamp/Conway 2-stream kickback transport for
gliders requires that the streams be synchronized so that they're all
ultimately annihilated.  How is the information and control to accomplish
this handled?

Perhaps my doubts only apply to their claim that a self-reproducing life 
configuration is possible (or one that can reproduce itself arbitrarily
far away).  I'm perfectly happy with their construction of a memory of
arbitrary capacity acheived by moving blocks in and out.
--
Scott Huddleston
scott@crl.labs.tek.com

From cellular-automata-request@Think.COM  Tue Feb 26 13:53:25 1991
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Date: Tue, 26 Feb 1991 13:48-0500
From: Allan C. Wechsler <ACW@YUKON.SCRC.Symbolics.COM>
Subject: Re: Berelekamp/Conway proof...
To: scott@ferrari.LABS.TEK.COM, ca@Think.COM
In-Reply-To: <7824@tekchips.LABS.TEK.COM>
Message-Id: <19910226184843.8.ACW@WHIMBREL.SCRC.Symbolics.COM>

It seems that your qualms about the argument in Winning Ways could cause
you to doubt the existence of a Constructor but not of a Computer.

From cellular-automata-request@Think.COM  Wed Feb 27 14:04:33 1991
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Date: Wed, 27 Feb 91 18:24:17 GMT
From: francis@hanauma.Stanford.EDU (Francis Muir)
Organization: Stanford University, Department of Geophysics
Subject: Modeling waves
Message-Id: <1991Feb27.182417.18236@morrow.stanford.edu>
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The following Advice recently appeared as a posting, and I offer a
commentary after the quote:

	Postdoctoral researchers sought for developing lattice gas
	models on a connection machine at the Naval Research
	Laboratory.  NRL is developing a lattice gas model for wave
	propagation, specifically for ocean acoustics.  A preliminary
	2-d model has simulated reflection, transmission and scattering
	processes accurately.  A 3-d model is under development.  The
	work is unclassified and publication is encouraged.  Much of
	the development is being done jointly with the Center for
	Nonlinear Studies at Los Alamos.

	For more information on the technical program contact:
        
		Dr. Susan K. Numrich, Code 5150
        	Naval Research Laboratory
        	Washington, DC 20375-5000        
		(202) 404-7345
        	numrich@cmsun.nrl.navy.mil

 
Is this connection machine a Connection Machine? A CM1 or CM2 (Logical
or Floating-point machine)? Is the Lattice Gas modeling the Navy has in
mind particle mechanical?  Statistical mechanical (Boltzmann)?
Linearised Boltzmann? Are not the problems the Navy has in mind really
elastic and anisotropic (e.g. the difficult muddy bottom case)? 

The casual reader of this group should be aware that there are two
quite distinct types of automata, the Lifelike and the lifelike.  The
former ruled by Chaos, and the latter by Conservation. Building
Automata to model physical processes usually modeled by PDE's makes
sense and it has an attraction all it's own, but be aware that it will
not be for those drawn to the mysteries of Chaos.  Modeling
conservative schemes with particles is quite instructive, but hardly
cost-efficient. The new class of massively parallel floating-point
machines (or special purpose probability machines) seem to have
relegated particle methods to the dark ages and Academia. 

On the other hand, and using a diminutive CM2 with no Data Vault and
Dark Ages (256K) memory chips, I can still get 20 turnarounds a morning
on my 2- and 3-D wave modeling in heterogeneous media using a
linearised Boltzmann scheme. This makes conceptual debugging a delight,
and is largely due to the excellent implementation of an extended
(FORTRAN90-like) compiler, and the Frame Buffer - a graphics monitor
hard-wired to the CM's plane of processors.

Cheers
							Philomath

UUCP: ...!decwrl!hanauma.stanford.edu!francis
INTERNET: francis@hanauma.stanford.edu                         

				This coloured counterfeit that thou beholdest,
				vainglorious with the excellencies of art,
				is, in fallacious syllogisms of colour,
				nought but a cunning dupery of sense;

						Juana de Asbaje y Rodrigues, 
							Sor Ines de la Crus

From cellular-automata-request@Think.COM  Fri Mar  1 16:29:20 1991
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To: "Allan C. Wechsler" <ACW@yukon.scrc.symbolics.com>
Cc: ca@Think.COM
Subject: Re: Berelekamp/Conway proof... 
In-Reply-To: Your message of Tue, 26 Feb 91 13:48:00 -0500
Date: Fri, 01 Mar 91 13:31:10 PST
From: scott@tekchips.labs.tek.com

> It seems that your qualms about the argument in Winning Ways could cause
> you to doubt the existence of a Constructor but not of a Computer.

Right.  Do you have any arguments or constructions either suppporting or
refuting their Constructor?

From cellular-automata-request@Think.COM  Sat Mar  2 06:09:59 1991
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Date: 2 Mar 91 06:09:50 GMT
From: bagchi@eecs.umich.edu (Ranjan Bagchi)
Organization: University of Michigan
Subject: How Intelligent are the Winning Ways?
Message-Id: <BAGCHI.91Mar2000950@snarf.eecs.umich.edu>
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	How well-regarded is the stuff in 'Winning Ways' by
Berkamp, Conway, and Guy?  Prior to looking at it, I was under the
impression that it was basically a book of recerational mathematics,
albeit with sound math behind it.  
	Anyway, I looked it up today because I'd heard of some work in
it screwing around with Conway's Life ;), and trying to show how to
build a computing machine with an appropriate configuration.
 
	Anyway...some of the initial proofs I have no problem with,
until the author mentions some wonderful things which a Life computer
could do, if there were some kind of closed form way to determine what
a given Life configuration would stabilize out to.   This is where I
balked... seeing that a Turing Machine is definitely constructable in Life
if you can do a computing machine, then the author just described the
Halting Problem, and treats it like it's something decidable.

	One last anyway... more for the cell-automata folks, but isn't
the method of constructing a computing machine gone about in the book
(basically modelling the E.E. approach to computer-building, using
gates and stuff) kinda un-natural?  I've only really just started
studying automata theory, but this strikes me as weird.
 
	-rj

	
	
--
--------------------------------------------------------------------------------
Ranjan Bagchi - At Large.  Well Kinda.  |  what kind of person
bagchi@[eecs                            |  would want to count syllables
        caen,                           |  just to write haiku?
	math.lsa].umich.edu     	|  
--------------------------------------------------------------------------------

From cellular-automata-request@Think.COM  Sat Mar  2 19:04:15 1991
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Date: 2 Mar 91 23:13:47 GMT
From: wlod@netcom.COM (Wlodzimierz Holsztynski)
Organization: Netcom - Online Communication Services  UNIX System {408 241-9760 guest}
Subject: Re: How Intelligent are the Winning Ways?
Message-Id: <26580@netcom.COM>
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In article <BAGCHI.91Mar2000950@snarf.eecs.umich.edu> bagchi@eecs.umich.edu (Ranjan Bagchi) writes:
>
>	How well-regarded is the stuff in 'Winning Ways' by
>Berkamp, Conway, and Guy?

Berkamp, Conway and Guy regard it very well.

	Wlodek

From cellular-automata-request@Think.COM  Mon Mar  4 11:04:54 1991
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Date: 4 Mar 91 13:23:09 GMT
From: armltd!dseal@bloom-beacon.MIT.EDU (David Seal)
Organization: Acorn Computers Ltd, Cambridge, England
Subject: Re: How Intelligent are the Winning Ways?
Message-Id: <5539@acorn.co.uk>
Newsgroups: rec.puzzles,sci.math,comp.theory.cell-automata
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In article <BAGCHI.91Mar2000950@snarf.eecs.umich.edu> bagchi@eecs.umich.edu
(Ranjan Bagchi) writes:

>
>       How well-regarded is the stuff in 'Winning Ways' by
>Berkamp, Conway, and Guy?  Prior to looking at it, I was under the
 ^^^^^^^
 Berlekamp, I believe.

>impression that it was basically a book of recerational mathematics,
>albeit with sound math behind it.  
>       Anyway, I looked it up today because I'd heard of some work in
>it screwing around with Conway's Life ;), and trying to show how to
>build a computing machine with an appropriate configuration.
> 
>       Anyway...some of the initial proofs I have no problem with,
>until the author mentions some wonderful things which a Life computer
>could do, if there were some kind of closed form way to determine what
>a given Life configuration would stabilize out to.   This is where I
>balked... seeing that a Turing Machine is definitely constructable in Life
>if you can do a computing machine, then the author just described the
>Halting Problem, and treats it like it's something decidable.

I'm afraid you're missing the point. The overall argument is:

   If there were a "closed form way" to determine the fate of a given Life
   configuration, then we could do all sorts of "wonderful things".

   But it is known that there are such things that we cannot do. Therefore
   there cannot be such a "closed form way".

The exact "wonderful thing we cannot do" to use is a matter of personal
choice. The authors use the known fact that there are undecidable problems
in number theory. Your argument uses the known fact that the Turing machine
halting problem is undecidable. There are all sorts of other arguments, all
more or less equivalent and all leading to the same conclusion.

I can see advantages to both arguments. Your argument about the Turing
machine is closer to what the Life computer actually is. However, I believe
the argument about undecidable problems in number theory is a better one for
the book: the authors can reasonably assume that anyone who has followed
them to that point in the book knows what a simple mathematical formula
means, but not that they know what a Turing machine is! So their particular
choice of argument probably makes the book some 10-20 pages shorter than
your one...

Incidentally, how would one go about building a Life Turing machine? I can
see one very long-winded technique, with a stationary tape and a moving
state machine: the state machine could move by emitting fleets of gliders to
(a) destroy itself; (b) reassemble an exact copy of itself one tape spacing
to the left or right. However, this seems like an awful lot of work: a
moving tape, stationary state machine Turing machine would seem a lot more
efficient. Any ideas how the moving tape might be constructed?

David Seal
dseal@acorn.co.uk

Standard disclaimers apply.

From cellular-automata-request@Think.COM  Mon Mar  4 11:51:37 1991
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Date: Mon, 4 Mar 1991 11:46-0500
From: Allan C. Wechsler <ACW@YUKON.SCRC.Symbolics.COM>
Subject: Re: Berelekamp/Conway proof... 
To: scott%tekchips.labs.tek.com@RELAY.CS.NET,
        ACW%yukon.scrc.symbolics.com@RELAY.CS.NET
Cc: ca@Think.COM
In-Reply-To: <9103012131.AA29527@tekchips.LABS.TEK.COM>
Message-Id: <19910304164649.9.ACW@WHIMBREL.SCRC.Symbolics.COM>

    Date: Fri, 1 Mar 1991 16:31 EST
    From: scott%tekchips.labs.tek.com@RELAY.CS.NET

    > It seems that your qualms about the argument in Winning Ways could cause
    > you to doubt the existence of a Constructor but not of a Computer.

    Right.  Do you have any arguments or constructions either suppporting or
    refuting their Constructor?

I'd have to refer you to Gosper -- RWG@Symbolics.COM.

From cellular-automata-request@Think.COM  Tue Mar  5 22:07:05 1991
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Date: 5 Mar 91 17:18:04 GMT
From: xanthian@zorch.SF-Bay.ORG (Kent Paul Dolan)
Organization: SF-Bay Public-Access Unix
Subject: Re: How Intelligent are the Winning Ways?
Message-Id: <1991Mar5.171804.1429@zorch.SF-Bay.ORG>
Newsgroups: rec.puzzles,sci.math,comp.theory.cell-automata
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In article <5539@acorn.co.uk> dseal@armltd.uucp (David Seal) writes:

> Incidentally, how would one go about building a Life Turing machine? I
> can see one very long-winded technique, with a stationary tape and a
> moving state machine: the state machine could move by emitting fleets
> of gliders to (a) destroy itself; (b) reassemble an exact copy of
> itself one tape spacing to the left or right. However, this seems like
> an awful lot of work: a moving tape, stationary state machine Turing
> machine would seem a lot more efficient. Any ideas how the moving tape
> might be constructed?

Won't work, or at least won't act like a Turing machine.

You have to be able to reverse direction on the tape.  Rebuilding the
head one space left rather than one space right is at least feasible,
but reversing the motion of a tape which is by definition infinite in
length is not.

Kent, the man from xanth.
<xanthian@Zorch.SF-Bay.ORG> <xanthian@well.sf.ca.us>

From cellular-automata-request@Think.COM  Wed Mar  6 02:04:44 1991
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Date: 5 Mar 91 11:49:47 GMT
From: jgk@osc.COM (Joe Keane)
Organization: Versant Object Technology, Menlo Park, CA
Subject: Re: How Intelligent are the Winning Ways?
Message-Id: <4654@osc.COM>
Newsgroups: rec.puzzles,sci.math,comp.theory.cell-automata
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In article <BAGCHI.91Mar2000950@snarf.eecs.umich.edu> bagchi@eecs.umich.edu
(Ranjan Bagchi) writes:
>	Anyway...some of the initial proofs I have no problem with,
>until the author mentions some wonderful things which a Life computer
>could do, if there were some kind of closed form way to determine what
>a given Life configuration would stabilize out to.   This is where I
>balked... seeing that a Turing Machine is definitely constructable in Life
>if you can do a computing machine, then the author just described the
>Halting Problem, and treats it like it's something decidable.

I think you're misinterpreting them.  They're just emphasizing the point that
the decision problem for Life is undecidable.

They claim that a Life computer can be programmed to spit out the first
solution to Fermat's Last Theorem, if one exists.  I wouldn't bet my life on
their construction, but i don't see any problem with it.  Then, if you had a
decision procedure for this computer, you'd know if FLT were true or false.

Some problems are undecidable in a contrived or artificial way.  Their point
is that Life is not like that, since it can include arbitrary Turing machines,
including universal ones.  If there were a decision procedure for Life, then
you could solve any mathematical problem.

From cellular-automata-request@Think.COM  Wed Mar  6 03:04:33 1991
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Date: 6 Mar 91 06:17:47 GMT
From: william@oreo.berkeley.edu (W. E. Grosso)
Organization: U.C. Berkeley Math. Department.
Subject: Re: Something for the ants to do
Message-Id: <1991Mar6.061747.6881@agate.berkeley.edu>
Newsgroups: comp.theory.cell-automata
References: <16mJX2w163w@shark.cs.fau.edu>
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I've just started reading this newsgroup. This discussion about ants 
seems interesting. Could people send me, privately, some 
info on what ants are ?

Thanks
William E. Grosso
(william@math.berkeley.edu)

From cellular-automata-request@Think.COM  Wed Mar  6 10:04:55 1991
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Date: 6 Mar 91 14:12:17 GMT
From: edp@jareth.enet.dec.com (Eric Postpischil (Always mount a scratch monkey.))
Organization: Digital Equipment Corporation
Subject: Re: How Intelligent are the Winning Ways?
Message-Id: <20805@shlump.nac.dec.com>
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In article <1991Mar5.171804.1429@zorch.SF-Bay.ORG>, xanthian@zorch.SF-Bay.ORG
(Kent Paul Dolan) writes:

[about creating a Turing machine in the universe of Conway's Life]

>You have to be able to reverse direction on the tape.  Rebuilding the
>head one space left rather than one space right is at least feasible,
>but reversing the motion of a tape which is by definition infinite in
>length is not.

What's been written to the tape is never actually infinite; reversing the motion
of the portion that has been written and marking the current ends is sufficient
to achieve the emulation.


				-- edp (Eric Postpischil)
				"Always mount a scratch monkey."
				edp@jareth.enet.dec.com

From cellular-automata-request@Think.COM  Thu Mar  7 09:47:40 1991
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Date: Thu, 7 Mar 91 06:29:15 MST
From: cgl@infidel.lanl.gov (Chris Langton)
Message-Id: <9103071329.AA08520@infidel.lanl.gov>
To: ca@Think.COM
Subject: Cellsim use in research?




To all Cellsim users:

  In order to justify continued work on Cellsim and its probable successor,
the Process-Gas Simulation System, I need references to any published
research that made use of Cellsim in any way.

  So, if you have used Cellsim in any research that has lead to a published
paper, please let me know and include the reference to the paper. I'd also
appreciate a reprint of the paper, if possible.

Thanks!


   Chris Langton

   Complex Systems Group
   MS B213, Theoretical Division	Phone: (505) 667-9471
   Los Alamos National Laboratory	Email: cgl@t13.lanl.gov
   Los Alamos, New Mexico, USA		FAX:   (505) 665-3003
   87545



From cellular-automata-request@Think.COM  Thu Mar  7 14:05:33 1991
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Date: 7 Mar 91 03:04:00 GMT
From: cjhs@minster.york.ac.uk
Organization: Department of Computer Science, University of York, England
Subject: Re: How Intelligent are the Winning Ways?
Message-Id: <668315039.11879@minster.york.ac.uk>
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in article <1991Mar5.171804.1429@zorch.SF-Bay.ORG>, xanthian@zorch.SF-Bay.ORG (Kent Paul Dolan) says:
> 
> In article <5539@acorn.co.uk> dseal@armltd.uucp (David Seal) writes:
>> Incidentally, how would one go about building a Life Turing machine? I

The method proposed in "Winning Ways" is to construct a machine which
has the same computational power as a turing machine, using counters
that can hold arbitrary integers. To build something corresponding
directly to a turing machine with an infinite tape...

>> can see one very long-winded technique, with a stationary tape and a
>> moving state machine: the state machine could move by emitting fleets
>> of gliders to (a) destroy itself; (b) reassemble an exact copy of
>> itself one tape spacing to the left or right. However, this seems like
>> an awful lot of work: a moving tape, stationary state machine Turing
>> machine would seem a lot more efficient. Any ideas how the moving tape
>> might be constructed?
> 
> Won't work, or at least won't act like a Turing machine.
> 
> You have to be able to reverse direction on the tape.  Rebuilding the
> head one space left rather than one space right is at least feasible,
> but reversing the motion of a tape which is by definition infinite in
> length is not.

Actually, I think it IS possible. What we may be able to do is
represent a finite tape which can be moved to the left and the right,
and also extended as necessary. As long as we insist that the infinite
tape is such that at any given time all symbols sufficiently far from
the read write head are OFF (or zero), then this extendible finite tape
is essentially the same thing.

We now come to a fun application of a remarkable pattern recently
posted to the net by Paul Callahan: <callahan@server.cs.jhu.edu>

This pattern is one which I would have said was impossible, until it
was explicitly provided. I have tried it out using Xlife, and it works
as advertised.

The pattern provided is a extendible delay loop. It is a pattern which
encodes some number of bits of information as an endlessly circling
ring of gliders, and by sending gliders at the pattern in appropriate
ways one can rewrite any bit, or (dig this!) INSERT an extra bit into
the stream.

We need two such delay loops to represent the tape, and a finite
control for the turing machine itself. The initial input tape is
encoded onto the initial delay loops, and must (of course) have only a
finite number of ON (or one) symbols.

The bits on the delay loop are grouped into pairs, so that four symbols
can be represented. They are HEAD, TAIL, ON, OFF. Each delay loop
always has exactly one HEAD symbol, one TAIL symbol, and some number of
ON and OFF symbols between them.

The symbol under the read write head of the tape is kept in the finite
control. The symbols on the tape to the "left" of the read write head
correspond (in order) to the symbols coming after the HEAD symbol on
the left hand delay loop. The TAIL symbol represents an infinite
sequence of OFF symbols. And analogously for the right hand side.

To move the tape to the left, the finite control acts as follows.  It
waits until the HEAD symbol is about to come around on the left hand
delay loop, then overwrites it with any symbol, and overwrites the
following symbol with HEAD. At the same time, this following symbol
must also be tested, and some signal sent back to the finite control
representing ON or OFF. Tricky co-ordination required here, but far
from impossible. At some point the delay stream must test for the HEAD
symbol, and then send a timing signal back to the finite control.

At the same time, the finite control must insert into the right hand
delay loop (after the HEAD symbol) the bit which is to replace the
symbol which was under the read write head.

Voila!

This turing machine has some unfortunate properties. In particular,
each step of the machine will take more life cycles than the step
before it. Even worse, the extendible delay loop grows very rapidly and
without limit, even if you are not inserting bits into it.  Thus any
implementation would bog down before the turing machine had executed
its first couple of cycles.

Even so, I am strongly of the opinion that a turing machine could be
implemented in life EXPLICITLY, and the pattern actually run with the
xlife program using a reasonable amount of memory. You just won't have
the patience to wait for it to do anything useful.

I don't want to spend the time to figure out the pattern. If anyone
else does, go for it. Don't forget to acknowledge Paul and myself when
you publish!

I have the pattern for Paul's extendible delay loop, if anyone needs it.
But I have lost his excellent comentary. So better you mail Paul first,
if you are interested.

Ciao -- Christopher Ho-Stuart
	University of York
	cjhs@uk.ac.york.minster     or possibly    cjhs@minster.york.ac.uk

From cellular-automata-request@Think.COM  Fri Mar  8 04:04:43 1991
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Date: 8 Mar 91 01:02:32 GMT
From: lhust@venus.phyast.pitt.edu (Li-Wei Hung)
Organization: University of Pittsburgh, Department of Physics and Astronomy
Subject: Test?
Message-Id: <100882@unix.cis.pitt.edu>
Newsgroups: rec.puzzles,sci.math,comp.theory.cell-automata
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This is a test

From cellular-automata-request@Think.COM  Sat Mar  9 03:07:43 1991
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Date: 8 Mar 91 20:30:20 GMT
From: unislc!ttobler@bloom-beacon.MIT.EDU (Trent Tobler)
Organization: unisys
Subject: Life Turing Machines (was Re: How Intelligent are the Winning Ways?)
Message-Id: <1991Mar8.203020.26148@unislc.uucp>
Newsgroups: rec.puzzles,sci.math,comp.theory.cell-automata
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From article <1991Mar5.171804.1429@zorch.SF-Bay.ORG>, by xanthian@zorch.SF-Bay.ORG (Kent Paul Dolan):
> In article <5539@acorn.co.uk> dseal@armltd.uucp (David Seal) writes:
> 
>> Incidentally, how would one go about building a Life Turing machine? I
>> can see one very long-winded technique, with a stationary tape and a
>> moving state machine: the state machine could move by emitting fleets
>> of gliders to (a) destroy itself; (b) reassemble an exact copy of
>> itself one tape spacing to the left or right. However, this seems like
>> an awful lot of work: a moving tape, stationary state machine Turing
>> machine would seem a lot more efficient. Any ideas how the moving tape
>> might be constructed?
> 
> Won't work, or at least won't act like a Turing machine.
> 
> You have to be able to reverse direction on the tape.  Rebuilding the
> head one space left rather than one space right is at least feasible,
> but reversing the motion of a tape which is by definition infinite in
> length is not.
> 

Another way is to have the state machine sent a fleet of gliders to the
tape reader, containing the information as to whether to move right or
left, and the symbol to write.  The tape reader would then send back a
fleet of gliders that represent the symbol found on the tape.

                      write symbol
  +--------+         and move left  +------+
  |State   |            >  >        | Tape |
  | Machine|             >          |Reader|
  +--------+                        +------+

                     o                  
                              o               <- tape symbols
                                       o 
 


  +--------+                        +------+
  |State   |                        | Tape |  Tape reader destroys old
  | Machine|                        |Reader|  symbol and writes a new one.
  +--------+                        +------+

                     o                 v
                              o       v
                                       o 
 


  +--------+               +------+
  |State   |               | Tape |    Tape reader moves then
  | Machine|               |Reader|    determines symbol on tape
  +--------+               +------+
                             v
                     o         v       o
                              o
                                         
 
 

  +--------+               +------+
  |State   |        <  <   | Tape |    And then sends the symbol
  | Machine|         <     |Reader|     back to the state machine
  +--------+               +------+
                            
                     o                 o
                              o
 


In this way, the tape can extend to infinity, any number of symbols can
be encoded, and the state machine can be a large as possible without the
complexity of moving it added.  The tape reader can be designed to detect
some special symbol called real-end-of-tape, and when it reads this,
it creates a new real-end-of-tape to the right, and writes a
virtual-end-of-tape at the current location.  Or another solution if the
number of symbols are known is to know the symbol with the longest response
time, and if nothing is heard back within that time, it sends an end-of-tape
signal.  This has the drawback that it sends off stray gliders into space.


As a side note, this machine literally crashes if you attempt to move
the tape reader left of the end-of-tape  ie. it collides with the
state machine creating a mess.  :)
---

   Trent Tobler - ttobler@csulx.weber.edu

From cellular-automata-request@Think.COM  Sun Mar 10 02:05:55 1991
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Date: Sat, 9 Mar 1991 21:16:29 GMT
From: ebert@parc.xerox.com (Robert Ebert)
Organization: Xerox SSU
Subject: Re: Life Turing Machines (was Re: How Intelligent are the Winning Ways?)
Message-Id: <1991Mar9.211629.29650@parc.xerox.com>
Newsgroups: rec.puzzles,sci.math,comp.theory.cell-automata
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>>> Incidentally, how would one go about building a Life Turing machine? I
>>> can see one very long-winded technique, with a stationary tape and a
>>> moving state machine...
>>> Any ideas how the moving tape might be constructed?
>> 
>> You have to be able to reverse direction on the tape.  Rebuilding the
>> head one space left rather than one space right is at least feasible,
>> but reversing the motion of a tape which is by definition infinite in
>> length is not.
>
>Another way is to have the state machine sent a fleet of gliders to the
>tape reader, containing the information as to whether to move right or
>left, and the symbol to write.  The tape reader would then send back a
>fleet of gliders that represent the symbol found on the tape.

I missed the beginning of this thread, but it appears that the challenge
is to build a real Turing machine, and not just a very good simulation.

One potential moving tape solution would be to use a "just in time" delivery
system on the tape.  That is, start with a short, finite tape and, when you
need a space that doesn't exist, enlarge the tape in that direction.  This
way the tape will never actually need to be infinitely long, at least, not in
any finite amount of time, and so the resources necessary to move the tape will
also be finite at any given time.

Of course, as we run out of matter and energy (about the time the universe
ends in a sea of luke-warm entropy) things will break down, but then, if
you need to build an infinite tape to start the "moving machine" version,
you'll never complete it and your machine will never even start processing.

Philosophically, isn't this what we're doing now?  As we need more computing
resources, we simply build them.  So, the, we (the intelligent creatures of the
universe) can be said to have infinite data storage capacity.  Hmm...

			--Bob



From cellular-automata-request@Think.COM  Mon Mar 11 02:05:35 1991
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Date: 11 Mar 91 06:36:31 GMT
From: infidel@maths.uwa.oz.au (INFIDEL)
Organization: University of Western Australia
Subject: complexity of CA
Message-Id: <1991Mar11.063631.12301@uniwa.uwa.oz>
Newsgroups: comp.theory.cell-automata
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I'm looking for any proofs showing that, say, certain 1-d CA are in the
class NP; i.e. complexity results about CA. I know that J. von Neumann
showed that the 2-d CA (Game of Life) is universal; I've also read about
analytical results by Odlyzko et. al. showing how future states of
certain "linear" 1-d CA can be calculated in advance without having to
go through the iterations. I heard a rumour that S Wolfram started a
journal on CA; unfortunately, out in the wilderness over here (Perth,
Western Australia) we have to rely on international pidgeon post for our
journals --- so I don't know if Wolfram's journal is dinkum.

I'd be grateful if a voice out yonder could confirm that the journal
exists; and if it does, if they could provide some contact address for
it. Finally, if anyone's heard of any connections between NP and CA,
holler out so's I can hear ya!

John Wojdylo
Department of Mathematics
University of Western Australia

Perth
Nice place, really.

 

From cellular-automata-request@Think.COM  Mon Mar 11 10:08:34 1991
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Date: 11 Mar 91 11:38:56 GMT
From: armltd!dseal@bloom-beacon.MIT.EDU (David Seal)
Organization: Acorn Computers Ltd, Cambridge, England
Subject: Re: How Intelligent are the Winning Ways?
Message-Id: <5717@acorn.co.uk>
Newsgroups: rec.puzzles,sci.math,comp.theory.cell-automata
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In article <1991Mar5.171804.1429@zorch.SF-Bay.ORG> xanthian@zorch.SF-Bay.ORG
(Kent Paul Dolan) writes:

>In article <5539@acorn.co.uk> dseal@armltd.uucp (David Seal) writes:
>
>> Incidentally, how would one go about building a Life Turing machine? I
>> can see one very long-winded technique, with a stationary tape and a
>> moving state machine: the state machine could move by emitting fleets
>> of gliders to (a) destroy itself; (b) reassemble an exact copy of
>> itself one tape spacing to the left or right. However, this seems like
>> an awful lot of work: a moving tape, stationary state machine Turing
>> machine would seem a lot more efficient. Any ideas how the moving tape
>> might be constructed?
>
>Won't work, or at least won't act like a Turing machine.
>
>You have to be able to reverse direction on the tape.  Rebuilding the
>head one space left rather than one space right is at least feasible,
>but reversing the motion of a tape which is by definition infinite in
>length is not.

Some vague thoughts I've had about a moving tape:

Suppose you have a pattern which can contain an arbitrarily long string of
data:

   A B C D ... Y Z

And that you can control it from its head to either shift the data outwards,
adding a new entry:

   A B C D ... Y Z
 ->nAB C D ... Y Z
 ->n ABC D ... Y Z
 ->n A BCD ... Y Z
 ->n A B CD... Y Z
 ->...
 ->n A B C ...XY Z
 ->n A B C ... XYZ
 ->n A B C ... X Y Z

Or to shift the data inwards, removing the head in the process:

   A B C D ... Y Z
 -> B  C D ... Y Z
 ->B  C  D ... Y Z
 ->B C  D  ... Y Z
 ->B C D  E... Y Z
 ->...
 ->B C D E ...Y  Z
 ->B C D E ...  Z
 ->B C D E ... Z

Then you could construct a moving tape out of two of these: you shift the
tape right by shifting its left half inwards and its right half outwards,
moving the symbol taken from the head of the left half on to the right half:

   z y ... d c b a   |   A B C D ... Y Z
 ->  z ... e d c b   |   a A B C ... X Y Z

You would of course need to take special action if the left hand side is
empty: this simply consists of pretending you read a "0" from the left hand
half-tape, extending the right hand half-tape with a "0", and not attempting
to shorten the left hand half-tape. Shifting the tape leftwards would be
similar.

An important part of this scheme is that the actual shift of the tape would
take place as a "wave" moving out along the tape at some constant speed, as
indicated in the diagrams above. Furthermore, provided both the "compression
wave" generated by shifting a tape half outwards and the "expansion wave"
generated by shifting a tape half inwards move at the same speed, you don't
have to wait for the tape movement to complete - you merely have to wait for
a suitable period to ensure that two successive waves don't interfere with
each other. This should be a constant amount of time, independent of the
length of the half-tape.

If you want a Turing machine implementation that runs at a reasonable
constant speed, something like this would seem to be the answer. The other
options I've seen by now are:

(a) The moving machine, stationary tape option referred to in my original
    message. Runs at a constant but VERY slow speed.

(b) The technique using extendible delay loops to simulated tape halves,
    described in a posting by Christopher Ho-Stuart. Runs at a non-constant
    speed, roughly inversely proportional to the size of the chunk of tape
    used so far.

(c) A technique described to me by email by Richard Schroeppel, which can be
    summarised as having a stationary tape and a stationary machine with a
    movable read/write head. He says it uses technology similar to that used
    for the sliding block memory to move the head and to read and write the
    contents of the tape. When reading the tape, two pulses are sent out:
    one is returned or not returned according to the contents of the tape,
    while the other is always returned and acts as a timing pulse. This
    again runs at a non-constant speed, this time roughly inversely
    proportional to the distance the tape head has moved from the state
    machine.

What I don't know is how to construct the half-tape required for my moving
tape. I suspect it's quite difficult!

David Seal
dseal@acorn.co.uk or dseal@armltd.uucp

Standard disclaimers apply.

From cellular-automata-request@Think.COM  Mon Mar 11 13:31:22 1991
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Date: 11 Mar 91 11:38:56 GMT
From: armltd!dseal@bloom-beacon.MIT.EDU (David Seal)
Organization: Acorn Computers Ltd, Cambridge, England
Subject: Re: How Intelligent are the Winning Ways?
Message-Id: <5717@acorn.co.uk>
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In article <1991Mar5.171804.1429@zorch.SF-Bay.ORG> xanthian@zorch.SF-Bay.ORG
(Kent Paul Dolan) writes:

>In article <5539@acorn.co.uk> dseal@armltd.uucp (David Seal) writes:
>
>> Incidentally, how would one go about building a Life Turing machine? I
>> can see one very long-winded technique, with a stationary tape and a
>> moving state machine: the state machine could move by emitting fleets
>> of gliders to (a) destroy itself; (b) reassemble an exact copy of
>> itself one tape spacing to the left or right. However, this seems like
>> an awful lot of work: a moving tape, stationary state machine Turing
>> machine would seem a lot more efficient. Any ideas how the moving tape
>> might be constructed?
>
>Won't work, or at least won't act like a Turing machine.
>
>You have to be able to reverse direction on the tape.  Rebuilding the
>head one space left rather than one space right is at least feasible,
>but reversing the motion of a tape which is by definition infinite in
>length is not.

Some vague thoughts I've had about a moving tape:

Suppose you have a pattern which can contain an arbitrarily long string of
data:

   A B C D ... Y Z

And that you can control it from its head to either shift the data outwards,
adding a new entry:

   A B C D ... Y Z
 ->nAB C D ... Y Z
 ->n ABC D ... Y Z
 ->n A BCD ... Y Z
 ->n A B CD... Y Z
 ->...
 ->n A B C ...XY Z
 ->n A B C ... XYZ
 ->n A B C ... X Y Z

Or to shift the data inwards, removing the head in the process:

   A B C D ... Y Z
 -> B  C D ... Y Z
 ->B  C  D ... Y Z
 ->B C  D  ... Y Z
 ->B C D  E... Y Z
 ->...
 ->B C D E ...Y  Z
 ->B C D E ...  Z
 ->B C D E ... Z

Then you could construct a moving tape out of two of these: you shift the
tape right by shifting its left half inwards and its right half outwards,
moving the symbol taken from the head of the left half on to the right half:

   z y ... d c b a   |   A B C D ... Y Z
 ->  z ... e d c b   |   a A B C ... X Y Z

You would of course need to take special action if the left hand side is
empty: this simply consists of pretending you read a "0" from the left hand
half-tape, extending the right hand half-tape with a "0", and not attempting
to shorten the left hand half-tape. Shifting the tape leftwards would be
similar.

An important part of this scheme is that the actual shift of the tape would
take place as a "wave" moving out along the tape at some constant speed, as
indicated in the diagrams above. Furthermore, provided both the "compression
wave" generated by shifting a tape half outwards and the "expansion wave"
generated by shifting a tape half inwards move at the same speed, you don't
have to wait for the tape movement to complete - you merely have to wait for
a suitable period to ensure that two successive waves don't interfere with
each other. This should be a constant amount of time, independent of the
length of the half-tape.

If you want a Turing machine implementation that runs at a reasonable
constant speed, something like this would seem to be the answer. The other
options I've seen by now are:

(a) The moving machine, stationary tape option referred to in my original
    message. Runs at a constant but VERY slow speed.

(b) The technique using extendible delay loops to simulated tape halves,
    described in a posting by Christopher Ho-Stuart. Runs at a non-constant
    speed, roughly inversely proportional to the size of the chunk of tape
    used so far.

(c) A technique described to me by email by Richard Schroeppel, which can be
    summarised as having a stationary tape and a stationary machine with a
    movable read/write head. He says it uses technology similar to that used
    for the sliding block memory to move the head and to read and write the
    contents of the tape. When reading the tape, two pulses are sent out:
    one is returned or not returned according to the contents of the tape,
    while the other is always returned and acts as a timing pulse. This
    again runs at a non-constant speed, this time roughly inversely
    proportional to the distance the tape head has moved from the state
    machine.

What I don't know is how to construct the half-tape required for my moving
tape. I suspect it's quite difficult!

David Seal
dseal@acorn.co.uk or dseal@armltd.uucp

Standard disclaimers apply.

From cellular-automata-request@Think.COM  Mon Mar 11 15:06:34 1991
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Date: 11 Mar 91 17:27:21 GMT
From: callahan@server.cs.jhu.edu (Paul Callahan)
Organization: JHU Computer Science Deparment, Baltimore MD
Subject: Re: How Intelligent are the Winning Ways?
Message-Id: <callahan.668718947@newton.cs.jhu.edu>
Newsgroups: rec.puzzles,sci.math,comp.theory.cell-automata
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In article <5717@acorn.co.uk> dseal@armltd.uucp (David Seal) writes:
[Some stuff about Life Turing Machines with constant slowdown in simulation]

It's interesting that this thread has gotten going now, since I posted
related material over two months ago that did not generate much commentary.
In a recent posting, Christopher Ho-Stuart referred to my construction of an 
extensible delay loop.  Unfortunately, as he and David Seal have pointed out, 
any TM simulation that used it would have a non-constant slowdown proportional
to the current size of the store. 

On the other hand, it *is* an explicit Life pattern (available in Xlife format),
and for this reason, I find it a little more satisfying than most of the general
schema that have been proposed.  It would not be all that hard to add a 
finite control and turn it into a universal machine, but I have not had the 
time recently.

However, if we are speaking of general approaches instead of explicit patterns, 
then there is a straightforward general method for constructing a constant time
simulation of an arbitrary 1-D cell automaton (with finite states per cell and
transition function based on left and right neighbors), and it doesn't take 
much imagination to see that this implies a constant time simulation of an 
arbitrary Turing Machine.

We first note that it is possible to construct any finite logic circuit with
glider guns, and that glider guns can be produced by a collision of gliders.
There is a construction called a "rake" (or a "glider puffer") that produces
a glider at regular intervals (like a gun) but which itself propagates 
either horizontally or vertically.  There is a technique for constructing 
rakes with arbitrarily long periods, which I discussed in some detail in
early January.  

It turns out that this last point was not well-known (i.e. not discovered
by Gosper in the early 70s), but essentially the same approach had been
discovered a little earlier by Dean Hickerson.  To make a long story short,
it is possible to construct a class of rakes whose period grows exponentially
with the size (measured either by cell population or area of bounding box) of 
the construction.  Again, I have an Xlife pattern that illustrates the 
technique, and if some kind reader wishes to dredge up the accompanying text
of my two articles about this pattern, I can repost.

The famous breeder pattern (see any Life reference) consists of a growing 
sequence of glider guns left in the wake of a flotilla of interacting rakes.  
As long as our rakes are of sufficiently long period, we can construct a 
sequence of finite logic cells in the same manner (modulo a few details about 
how to get the logic cells in the right initial state).  The logic cells 
are themselves composed of glider guns, so the gliders-->glider-gun collision  
is all we really need.

Our 1-D cell automaton consists of an infinite sequence of cells lying along a 
horizontal line.  They are initially quiescent with the exception of a finite
interval around the origin (call these the active cells).  We allow cells to 
wake up neighbors and send symbols back and forth, with the internal state 
changing according to some transition function.  

In the Life construction, logic cells would interact by sending gliders to 
their neighbors.  Gliders, of course, propagate diagonally, not horizontally, 
but we may get around this by leaving a trail of "shuttles" (also constructable
by a glider collision), parallel to the cells, to reflect the gliders 90 
degrees back to the horizontal axis (details left as an exercise).  
Alternatively, we can use horizontally propagating "spaceships" to carry 
information, as these can be produced in the logic cell using appropriate glider
collisions.

To construct a Life pattern corresponding to such an automaton with a given
initial configuration, we construct the active cells explicitly (note there 
are finitely many) and we develop two rake flotillas to build the infinite 
sequences of quiescent cells to the left and right (note that we could 
get away with an automaton that is infinite in just one direction). 

The rake flotillas move at half the "speed of light," so the sequence of
new cells is produced very rapidly.  As long as the propagation of data
between the cells is slower (and it will be), we are guaranteed that before
any cell tries wake up its neighbor, it will, in fact, have a neighbor to 
wake up. 

The number of steps it takes to compute the transition function in the
logic cell gives us the constant slowdown.  Otherwise, the pattern is a direct
simulation of an arbitrary 1-D cell automaton.  The catch is that we
need a rake for every glider to make the logic cell, and a cell may
require hundreds of gliders even if its transition function is quite simple.
Thus, our rake flotillas consist of very large (but finite) populations of 
cells.

However, all of the pieces (logic cells, rakes) can be easily constructed 
explicitly, so it is not as bad as a simulation that relies on universal 
constructors.  The essential difference is that rake flotillas are 
pre-programmed constructors that perform a very specific job.  Hence, they 
are much easier to design than universal constructors.

I believe that with a suitable encoding scheme in which rakes are treated
as aggregrates identified by position and phase-shift (rather than cell
populations), it would be possible to explicitly construct and verify such a 
pattern using readily available computational power (e.g. a desktop 
workstation).  If we had some CAD tools along the lines of "silicon compilers" 
for Life logic, then the design process would be much easier.  Of 
course, all of this is merely a question of filling in the details of proofs
that are generally agreed upon.  Besides the simple pleasure of building  
a machine and watching it click and whir, there may be little merit to 
such activity.

--
Paul Callahan
callahan@cs.jhu.edu

From cellular-automata-request@Think.COM  Tue Mar 12 01:06:31 1991
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Date: 12 Mar 91 04:26:15 GMT
From: mburke@eecs.wsu.edu (Matthew Burke - grad student)
Organization: Washington State University, Pullman
Subject: CA, predator-prey and other things
Message-Id: <1991Mar12.042615.17019@eecs.wsu.edu>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM


I would be intersted to any references people have about using CAs to
model ecological/biological systems.

The only things that I have been able to turn up so far are predator-prey
models.  I thought I had heard about other systems being modeled but have
yet to find any write-ups.

Please e-mail responses to me.  I will post a summary if sufficient
interest exists.


Thanks,
Matt Burke
mburke@yoda.eecs.wsu.edu
-- 
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%      Matthew M. Burke        mburke@yoda.eecs.wsu.edu    %
%   Where am I and what am I doing in this handbasket?     %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

From cellular-automata-request@Think.COM  Tue Mar 12 14:05:56 1991
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Date: 12 Mar 91 15:50:51 GMT
From: xanthian@zorch.SF-Bay.ORG (Kent Paul Dolan)
Organization: SF-Bay Public-Access Unix
Subject: Re: How Intelligent are the Winning Ways?
Message-Id: <1991Mar12.155051.16488@zorch.SF-Bay.ORG>
Newsgroups: sci.math,comp.theory.cell-automata,alt.flame,rec.puzzles
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dseal@armltd.uucp (David Seal) writes:
> xanthian@zorch.SF-Bay.ORG (Kent Paul Dolan) writes:

> dseal@armltd.uucp (David Seal) writes:
>
>> Incidentally, how would one go about building a Life Turing machine? I
>> can see one very long-winded technique, with a stationary tape and a
>> moving state machine: the state machine could move by emitting fleets
>> of gliders to (a) destroy itself; (b) reassemble an exact copy of
>> itself one tape spacing to the left or right. However, this seems like
>> an awful lot of work: a moving tape, stationary state machine Turing
>> machine would seem a lot more efficient. Any ideas how the moving tape
>> might be constructed?

>Won't work, or at least won't act like a Turing machine.

By which I should have clarified that I meant that in terms of the
number of cycles needed to complete an operation, operations that have
the same order statististics for a Turing machine have very different
order statistics for the moving tape case in Life. Example: move right
writing a symbol into each blank frame "forever", and doing that but
pausing one "step" time at each frame are both order N time operations
in the number N of frames traversed on a Turing machine. The first is
still order N on a moving tape Life emulation of a Turing machine, but
the second is (at least) order N*N, since the emulation has to wait for
the cessession/resumption of motion to reach the (ever more distant)
left end of the tape and report back between each pair of steps.

>You have to be able to reverse direction on the tape.  Rebuilding the
>head one space left rather than one space right is at least feasible,
>but reversing the motion of a tape which is by definition infinite in
>length is not.

And as several folks have written me, the unwritten piece of the tape
can be implicit, so only a finite tape need be considered in real use.
This doesn't remove the objection that what you end up with doesn't
have behavior subject to the same analysis as a "real" Turing machine.

> Some vague thoughts I've had about a moving tape:

> Suppose you have a pattern which can contain an arbitrarily long
> string of data:

>    A B C D ... Y Z

> And that you can control it from its head to either shift the data outwards,
> adding a new entry:

>    A B C D ... Y Z
>  ->nAB C D ... Y Z
>  ->n ABC D ... Y Z
>  ->n A BCD ... Y Z
>  ->n A B CD... Y Z
>  ->...
>  ->n A B C ...XY Z
>  ->n A B C ... XYZ
>  ->n A B C ... X Y Z

> Or to shift the data inwards, removing the head in the process:

>    A B C D ... Y Z
>  -> B  C D ... Y Z
>  ->B  C  D ... Y Z
>  ->B C  D  ... Y Z
>  ->B C D  E... Y Z
>  ->...
>  ->B C D E ...Y  Z
>  ->B C D E ...  Z
>  ->B C D E ... Z

> Then you could construct a moving tape out of two of these: you shift the
> tape right by shifting its left half inwards and its right half outwards,
> moving the symbol taken from the head of the left half on to the right half:

>    z y ... d c b a   |   A B C D ... Y Z
>  ->  z ... e d c b   |   a A B C ... X Y Z

> You would of course need to take special action if the left hand side
> is empty: this simply consists of pretending you read a "0" from the
> left hand half-tape, extending the right hand half-tape with a "0",
> and not attempting to shorten the left hand half-tape. Shifting the
> tape leftwards would be similar.

> An important part of this scheme is that the actual shift of the tape
> would take place as a "wave" moving out along the tape at some
> constant speed, as indicated in the diagrams above. Furthermore,
> provided both the "compression wave" generated by shifting a tape half
> outwards and the "expansion wave" generated by shifting a tape half
> inwards move at the same speed, you don't have to wait for the tape
> movement to complete - you merely have to wait for a suitable period
> to ensure that two successive waves don't interfere with each other.
> This should be a constant amount of time, independent of the length of
> the half-tape.

But the capability to move that wave down the tape is the capability to
record and erase an arbitrary current state, remember and write the
previous state, and move one step; i.e., pretty much the capabilities of
the moving head of an (at least) alphabet*alphabet state Turing machine.
If you can send that wave, whatever means you use to promulgate it is
pretty much the functional equivalent of the thing you were trying to
use it to replace, a moving head. Being that close to solving the
problem of a moving head that rebuilds itself with saved stateone step
left or right, it looks simpler to finish the job than to build an
immobile head which can also build this moving "almost a head" in two
versions.

I don't see that solving the problem, more making it worse, but I'm
willing to listen.

Kent, the man from xanth.
<xanthian@Zorch.SF-Bay.ORG> <xanthian@well.sf.ca.us>

From cellular-automata-request@Think.COM  Wed Mar 13 10:05:53 1991
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Date: 13 Mar 91 09:53:32 GMT
From: econrad@cs.wright.edu (Eric Conrad)
Organization: Wright State University
Subject: Re: How Intelligent are the Winning Ways?
Message-Id: <1991Mar13.095332.7152@cs.wright.edu>
Newsgroups: comp.theory.cell-automata
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From article <1991Mar12.155051.16488@zorch.SF-Bay.ORG>, by xanthian@zorch.SF-Bay.ORG (Kent Paul Dolan):
> By which I should have clarified that I meant that in terms of the
> number of cycles needed to complete an operation, operations that have
> the same order statististics for a Turing machine have very different
> order statistics for the moving tape case in Life. Example: move right
> writing a symbol into each blank frame "forever", and doing that but
> pausing one "step" time at each frame are both order N time operations
> in the number N of frames traversed on a Turing machine. The first is
> still order N on a moving tape Life emulation of a Turing machine, but
> the second is (at least) order N*N, since the emulation has to wait for
> the cessession/resumption of motion to reach the (ever more distant)
> left end of the tape and report back between each pair of steps.

(1) Analysis of the time complexity of a TM implementation is in terms
of TM transitions.  No assumptions need to be made about the
underlying time complexity of individual transitions.

(2) If the analysis of Life transitions is correct, it would appear
that the Life simulation of a TM preserves polynomial time
complexity.  More specifically, if the time complexity of a Turing
machine measured in TM transitions is f(n), bounded above by
some polynomial P(n), then the complexity measured in Life transitions
is O(P(n^2)).
 
-- 
-- Eric Conrad - Wright State University

A great many people think they are thinking when they
are merely rearranging their prejudices.  -- William James

From cellular-automata-request@Think.COM  Thu Mar 14 12:06:52 1991
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Date: 14 Mar 91 05:44:24 GMT
From: armltd!dseal@bloom-beacon.MIT.EDU (David Seal)
Organization: Acorn Computers Ltd, Cambridge, England
Subject: Re: How Intelligent are the Winning Ways?
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In article <1991Mar12.155051.16488@zorch.SF-Bay.ORG>
xanthian@zorch.SF-Bay.ORG (Kent Paul Dolan) writes:

>But the capability to move that wave down the tape is the capability to
>record and erase an arbitrary current state, remember and write the
>previous state, and move one step; i.e., pretty much the capabilities of
>the moving head of an (at least) alphabet*alphabet state Turing machine.
>If you can send that wave, whatever means you use to promulgate it is
>pretty much the functional equivalent of the thing you were trying to
>use it to replace, a moving head. Being that close to solving the
>problem of a moving head that rebuilds itself with saved stateone step
>left or right, it looks simpler to finish the job than to build an
>immobile head which can also build this moving "almost a head" in two
>versions.

Yes, I agree that the capabilities of a tape cell as I described it are
roughly the same as those of a moving head, or quite possibly even more
complicated. I'm not recommending the moving tape machine as a particularly
easy way to construct a Life Turing machine.

But what I was wondering about was the possibility of producing a constant
rate Turing machine - i.e. one for which you can say "One step of the Turing
machine always takes exactly C Life generations, where C is a known
constant". The moving head implementation does not meet this criterion: it
can take an arbitrary amount of time for data being written to get to the
head and for data being read to return from the head. The moving tape
implementation *could* have this property, provided a suitable tape could be
designed, because of the possibility of being able to start the movement of
the tape, wait a constant amount of time to let the movement wave go far
enough that it is not going to interfere with whatever you're doing at the
moment or with further movement waves, then proceed.

Paul Callahan's postings now indicate that this can be done, by using rakes
either to construct a 1-D cellular automaton (his suggestion) or a moving
tape (my suggestion, in a separate posting).

David Seal

Preferred email address is "dseal@armltd.uucp". Please use "dseal@acorn.co.uk"
instead if this doesn't succeed - "armltd.uucp" is not known everywhere yet.

From cellular-automata-request@Think.COM  Thu Mar 14 12:06:58 1991
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Date: 14 Mar 91 05:44:19 GMT
From: armltd!dseal@bloom-beacon.MIT.EDU (David Seal)
Organization: Acorn Computers Ltd, Cambridge, England
Subject: Re: How Intelligent are the Winning Ways?
Message-Id: <5822@acorn.co.uk>
Newsgroups: rec.puzzles,sci.math,comp.theory.cell-automata
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In article <callahan.668718947@newton.cs.jhu.edu> callahan@cs.jhu.edu (Paul
Callahan) writes:

>In article <5717@acorn.co.uk> dseal@armltd.uucp (David Seal) writes:
>[Some stuff about Life Turing Machines with constant slowdown in simulation]
>
>It's interesting that this thread has gotten going now, since I posted
>related material over two months ago that did not generate much commentary.

I've only recently found and started reading this group, because of the
crossposting of this thread to sci.math!

>However, if we are speaking of general approaches instead of explicit patterns, 
>then there is a straightforward general method for constructing a constant time
>simulation of an arbitrary 1-D cell automaton (with finite states per cell and
>transition function based on left and right neighbors), and it doesn't take 
>much imagination to see that this implies a constant time simulation of an 
>arbitrary Turing Machine.
>
>We first note that it is possible to construct any finite logic circuit with
>glider guns, and that glider guns can be produced by a collision of gliders.
>There is a construction called a "rake" (or a "glider puffer") that produces
>a glider at regular intervals (like a gun) but which itself propagates 
>either horizontally or vertically.  There is a technique for constructing 
>rakes with arbitrarily long periods, which I discussed in some detail in
>early January.

...

>Our 1-D cell automaton consists of an infinite sequence of cells lying along a 
>horizontal line.  They are initially quiescent with the exception of a finite
>interval around the origin (call these the active cells).  We allow cells to 
>wake up neighbors and send symbols back and forth, with the internal state 
>changing according to some transition function.  

...

>To construct a Life pattern corresponding to such an automaton with a given
>initial configuration, we construct the active cells explicitly (note there 
>are finitely many) and we develop two rake flotillas to build the infinite 
>sequences of quiescent cells to the left and right (note that we could 
>get away with an automaton that is infinite in just one direction). 

... 

>The number of steps it takes to compute the transition function in the
>logic cell gives us the constant slowdown.  Otherwise, the pattern is a direct
>simulation of an arbitrary 1-D cell automaton.  The catch is that we
>need a rake for every glider to make the logic cell, and a cell may
>require hundreds of gliders even if its transition function is quite simple.
>Thus, our rake flotillas consist of very large (but finite) populations of 
>cells.

Interesting idea. However, rather than using the 1-D cellular automaton
directly to simulate the Turing machine, why not just use the same idea to
generate a moving tape?

In other words, produce something like the following:


                          +-----------------+
                          |State machine for|
                          | Turing machine  |
                          +-----------------+
                                   |
                                   |
                                   |
                             +-----------+
                             |  Special  |
           +----+   +----+   | read/write|   +----+   +----+
    ... ---|Cell|---|Cell|---|    cell   |---|Cell|---|Cell|--- ...
           +----+   +----+   +-----------+   +----+   +----+


with the rows of cells being generated by rakes disappearing into the
distance, as in your suggestion.

I haven't worked out a detailed state diagram for the cells being generated,
but it should be fairly simple. Essentially, the two halves of the tape are
mirror images of each other. Each cell can contain no bits, one bit, or two
bits. No bit cells would grab the bit from the next cell out along the tape,
converting it to a no bit cell, while one bit cells would be passive and two
bit cells would force their outermost bit into the next cell out along the
tape, converting it into a two bit cell. To ensure that everything worked
smoothly, I suspect the tape state machine would have to cycle at something
like twice the speed of the Turing state machine.

Overall, I'm fairly certain such a tape would require a lot less logic per
cell than a 1-D cellular automaton that is capable of simulating a Turing
machine. This would presumably make designing and setting up a suitable
pattern of rakes considerably easier!

>... Of 
>course, all of this is merely a question of filling in the details of proofs
>that are generally agreed upon.  Besides the simple pleasure of building  
>a machine and watching it click and whir, there may be little merit to 
>such activity.

Yes, indeed. I enjoy simple pleasures! :-)

In fact, I even enjoy the thought experiments involved in working out how
one might go about doing such a design, regardless of whether the details
are ever filled in.

David Seal

Preferred email address is "dseal@armltd.uucp". Please use "dseal@acorn.co.uk"
instead if this doesn't succeed - "armltd.uucp" is not known everywhere yet.

From cellular-automata-request@Think.COM  Sat Mar 16 05:07:50 1991
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Date: 15 Mar 91 15:17:02 GMT
From: nsi91@parix.imag.fr (Pierre Bessiere)
Organization: IMAG Institute, University of Grenoble, France
Subject: Ecole de printemps NSI91
Message-Id: <19221@imag.imag.fr>
Newsgroups: comp.theory.cell-automata,comp.theory.dynamic-sys,comp.theory.self-org-sys,comp.ai.philosophy,comp.ai
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                    Ecole de printemps

                          NSI 91

		     Derniere annonce

          Neurosciences et Sciences de l'Ingenieur

              Villars de Lans (Isere, FRANCE)
                   du 13 au 17 mai 1991
                                

Depuis 1982 ont lieu, toutes les annees paires, les journees "Neurosciences 
et Sciences de l'Ingenieur". Pluri-disciplinarite, francophonie et mobilite 
en ont ete les maitres mots depuis leur creation. Les 5emes journees ont 
eu lieu en 1990 a Aussois et ont remporte un vif succes. En 
consequence, deux decisions furent prises par les participants : creer 
une association NSI et organiser, les annees impaires, en alternance avec 
les journees, des cours dans les divers domaines concernes.

Nous sommes heureux de vous apprendre, d'une part, que l'association vient 
de voir le jour et, d'autre part, que sa premiere tache a ete 
l'organisation de l'ecole de printemps qui se tiendra en mai 1991 
a Villars de Lans.

La vocation de ce cours est triple :
-	permettre a des chercheurs confirmes d'approfondir leurs 
connaissances sur certaines disciplines connexes a la leur;
-	permettre a de jeunes chercheurs (etudiants en these) une 
initiation rapide aux sciences de la cognition;
-	enfin, permettre a des industriels l'acces a un panorama de 
certaines des recherches en cours.

Le cours aura une duree de 4 jours et demi (8 demi-journees de travail 
+ une demi-journee de detente). La duree de chaque session sera de 
4 heures : 3 heures d'expose + 1/2 heure de pause + 1/2 heure de discussion. 

                           PROGRAMME :
                          -------------

Lundi : 
-------
Theme de la journee :  rappels des notions fondamentales. 
Cette journee comporte deux sessions en parallele: les rappels des 
notions fondamentales de neurosciences destines aux ingenieurs et 
reciproquement, les rappels sur les reseaux de neurones formels 
destines aux specialistes des neurosciences.

9h30 -> 13h : 

LE NEURONE ET LA SYNAPSE
     P. Gogan 

RESEAUX DE NEURONES FORMELS SUPERVISES 
     F. Blayo

15h -> 19h :

STRUCTURES ANATOMIQUES DU SYSTEME NERVEUX 
     P. Mouchet

RESEAUX DE NEURONES FORMELS NON SUPERVISES 
     C. Jutten

Mardi : 
-------
Theme de la journee : Vision

9h -> 13h : SYSTEMES VISUELS BIOLOGIQUES 
     Y. Fregnac 

15h -> 19h : RESEAUX DE NEURONES ET RECONNAISSANCE DES FORMES 
     L. Personnaz

Mercredi : 
----------
Theme de la 1/2 journee : Applications industrielles

9h -> 13h : LES APPLICATIONS INDUSTRIELLES DES RESEAUX DE NEURONES 
Thomson ; C.E.A. ; Philips

Jeudi : 
-------
Theme de la journee : Methodes

9h -> 13h : METHODES EXPERIMENTALES POUR L'ETUDE DES RESEAUX 
DE NEURONES BIOLOGIQUES 
     Y. De Ribaupierre et F. Nagy 

15h -> 19h : METHODES MATHEMATIQUES POUR L'ETUDE DES 
RESEAUX DE NEURONES FORMELS 
     J. Demongeot

Vendredi :
----------
Theme de la 1/2 journee : Ouverture sur des disciplines connexes

9h -> 13h : INTELLIGENCE ARTIFICIELLE SYMBOLIQUE VERSUS 
CONNEXIONISME SUB-SYMBOLIQUE 
     B. Amy et C. Robert

Le mercredi apres-midi est reserve a la detente : activites sportives et 
touristiques seront proposees.

Un support de cours sera fourni a chaque personne inscrite.

En marge de ce cours, des "sessions posters" sont prevues, ainsi 
que des salons de discussion organises par themes. L'idee etant 
essentiellement de permettre aux etudiants en these, a qui ce cours 
est tout particulierement destine, de pouvoir 
exposer leurs idees (meme si elles n'ont pas une maturite suffisante 
pour etre publiees), et d'avoir l'opportunite de discuter de ces 
idees avec des chercheurs confirmes. D'autres supports que les posters, 
par exemple bandes videos ou demonstrations de logiciels, seront 
accueillis volontiers dans ce cadre dans la mesure des 
possibilites techniques.

Il est aussi envisage d'organiser, un soir, une conference - debat 
de nature plus philosophique. Sujet et intervenants restent 
a determiner.

Le programme du cours a ete compose sous l'egide d'un comite pedagogique 
de neuf membres representant les differentes disciplines concernees.

Comite pedagogique :
--------------------
J. Bullier, INSERM -U94-, Lyon
D. Collobert, CNET, Lannion
A. Germond, EPFL, Lausanne
J. Herault, TIRF/INPG/UJF, Grenoble
R. Pesti, ITMI, Grenoble
P. Puget, DLETI/CENG/CEA, Grenoble
J. de Ribaupierre, Inst. de physiologie, Lausanne
G. Tiberghien, Lab. de Psycho. Experimentale, Grenoble
F. Vallet, LCR/Thomson-CSF, Paris

L'organisation a, quant a elle, ete confiee aux personnes suivantes:

Comite d'organisation :
-----------------------
F. Berthommier, TIMB/IMAG, Grenoble
P. Bessiere, LGI/IMAG, Grenoble
P. Demartines, LAMI/EPFL, Lausanne
A. Guerin, TIRF/INPG, Grenoble

Site :
------

Villars de Lans est une magnifique petite ville de montagne situee au 
coeur du massif du Vercors a 35 kilometres de Grenoble.

Hebergement :
-------------

L'hebergement aura lieu a la residence de tourisme Le Grand Adret 
en chambre a deux lits, comprenant douche et WC. Les personnes 
souhaitant etre hebergees dans une chambre simple devront 
acquitter un supplement de 1000 FF. 

Repas :
-------

Les petits dejeuners seront pris a la residence d'acceuil, 
les dejeuners dans un restaurant pres de la salle de conference 
et les diners au choix dans l'un des nombreux restaurants de la 
ville, chaque participant recevant un ticket restaurant de 70 FF 
par diner. Attention : le diner de dimanche n'est pas prevu.

Tarifs :
--------

Les prix s'entendent tout compris : frais d'inscription a la conference, 
support de cours, cinq nuits d'hotel (a partir de dimanche soir), 
pension complete (du lundi matin  au vendredi midi). 

Paiement a l'ordre de : Agent Comptable INPG (NSI91)
                        ----------------------------

Toute inscription devra imperativement etre accompagnee d'un 
reglement ou d'un bon de commande pour pouvoir etre prise en compte.

Transport :
-----------

Une navette partira le dimanche soir a 21H de la gare routiere 
de Grenoble (a cote de la gare SNCF). Le prix de cette navette 
est compris dans les frais d'inscription, en revanche, tout 
autre mode de transport sera a la charge de la personne concernee.

Adhesion a l'association NSI :
------------------------------

La cotisation a l'association est de 100 FF. Tout adherent de 
l'association se voit octroyer une remise de 100 FF sur 
le tarif du cours.

L'adhesion a une association devant etre un acte volontaire, 
nous vous prions d'indiquer clairement votre desir d'adherer 
sur le formulaire d'inscription.


Adresse :
---------                            Ecole de printemps NSI91
                                     LGI / IMAG (P. Bessiere)
                                     BP53X
                                     38041 Grenoble Cedex
                                     FRANCE

                                     nsi91@parix.imag.fr
                                     Fax : (33)76.44.66.75.
                                     Telex : UJF 980 134 F


----------------------------------------------------------------------
                          INSCRIPTION A NSI91
                    (A envoyer a l'adresse ci dessus)

Nom :
Prenom :
Organisme ou societe :
Adresse :



Telephone :
Fax :
E-mail :

                          --------------------

              <15/01/91     <30/03/91     >15/03/91

Etudiant :        O             O             O (Cocher la case convenable)
                2000FF        2250FF        2500FF

Chercheur :       O             O             O
                2500FF        2750FF        3000FF

Industriel :      O             O             O
                3500FF        4000FF        4500FF

Supplement chambre individuelle :     O
                                    1000FF

                          ---------------------
                       ADHESION A L'ASSOCIATION NSI

Si vous voulez adherer ecrire en toutes lettres
"Je desire adherer a l'association NSI" et signer :




----------------------------------------------------------------------

From cellular-automata-request@Think.COM  Sat Mar 16 06:06:21 1991
Received: by mail.think.com; Sat, 16 Mar 91 06:06:23 -0500
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Date: 16 Mar 91 07:00:45 GMT
From: pattis@cs.washington.edu (Richard Pattis)
Organization: U of Washington, Computer Science, Seattle
Subject: PC Products: Fractals, Chaos, Cellular Automata
Message-Id: <15483@june.cs.washington.edu>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM

Is there any list (in a FAQ file) of available PC software concerning
Fractals, Chaos, and/or Cellular Automata.  For one example, I recall
a CA package by Rudy Rucker but have forgotton the details.

Rich Pattis

From cellular-automata-request@Think.COM  Sat Mar 16 09:06:51 1991
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Date: 16 Mar 91 01:10:14 GMT
From: jgk@osc.COM (Joe Keane)
Organization: Versant Object Technology, Menlo Park, CA
Subject: Re: How Intelligent are the Winning Ways?
Message-Id: <4671@osc.COM>
Newsgroups: comp.theory.cell-automata
References: <1991Mar5.171804.1429@zorch.SF-Bay.ORG>, <5717@acorn.co.uk>, <1991Mar12.155051.16488@zorch.SF-Bay.ORG>
Sender: ca-request@Think.COM
To: ca@Think.COM

A Turing Machine is just a special case of a one-dimenstional cellular
automaton.  We can consider a Turing machine to have tape states and control
states, where there is always exactly one instance of the latter.  The control
states and tape states can be added together or multiplied, it's not really
important.

How do we do this in Life?  We want the tape patterns to be something that
doesn't move around, for example configurations of blocks are fine.  We can
also use blinkers or something that flips between states because we probably
have constraints on what time we'll look at it.

We want the control patterns to be something which interacts with the tape
patterns in some predictable way.  An operation of the Turing machine consists
of a control pattern interacting with a neighboring tape pattern.  A new
control pattern is created where the tape pattern was, and a new tape pattern
is left where the control pattern was.

It's not clear how to construct such control patterns in a direct way.  In
general, two arbitrary patterns will not interact in a nice way, instead
they'll make a mess.  But you could try a lot of possibilities for control and
tape patterns, and reject the ones that produce undesirable interactions.  It
seems that if you try enough, you may be able to come up with a small subset
with only desirable interactions.  As far as i know, no one has done this, but
i think it'd be a good area for Life hackers to explore.

You may know that certain combinations of tape and control states can't occur
in your Turing machine.  You can take advantage of this to simplify the
construction of your control states.  Then if there's a programming error and
one of these forbidden combinations occurs, the machine may self-destruct.

With Life we have an additional advantage that it's two-dimensional.  So maybe
we can put the control states above the tape states.  I don't know if this
gains you anything, but it's fun to think about a big complicated control
spaceship flying over a long row of tape patterns.  The spaceship can fire
gliders or scout ships at the tape pattern and analyze what returns to decide
what to do next.

Note we don't really have to worry about constructing an arbitrary Turing
machine.  We only need to find a way to make one universal Turing machine.
This UTM could even have its program on a separate tape, given that we have a
lot of space.
--
Joe Keane, amateur mathematician

From cellular-automata-request@Think.COM  Sat Mar 16 12:56:17 1991
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Date: 16 Mar 91 07:00:45 GMT
From: pattis@cs.washington.edu (Richard Pattis)
Organization: U of Washington, Computer Science, Seattle
Subject: PC Products: Fractals, Chaos, Cellular Automata
Message-Id: <15483@june.cs.washington.edu>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM

Is there any list (in a FAQ file) of available PC software concerning
Fractals, Chaos, and/or Cellular Automata.  For one example, I recall
a CA package by Rudy Rucker but have forgotton the details.

Rich Pattis

From cellular-automata-request@Think.COM  Sat Mar 16 13:06:17 1991
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Date: 16 Mar 91 16:12:17 GMT
From: callahan@server.cs.jhu.edu (Paul Callahan)
Organization: JHU Computer Science Deparment, Baltimore MD
Subject: Re: How Intelligent are the Winning Ways?
Message-Id: <callahan.669140176@newton.cs.jhu.edu>
Newsgroups: comp.theory.cell-automata,sci.math
References: <5717@acorn.co.uk>, <1991Mar12.155051.16488@zorch.SF-Bay.ORG>, <4671@osc.COM>
Sender: ca-request@Think.COM
To: ca@Think.COM

In article <4671@osc.COM> jgk@osc.COM (Joe Keane) writes:
> [stuff about simulating a 1-D CA in Life]
>How do we do this in Life?  

Actually, I thought I did a passable job of explaining how several postings ago.
Basically, we know enough about Life to construct arbitrary finite state 
machines out of glider guns (usable as cells).  And it is possible to develop 
specific constructors for arbitrary collections of glider guns.  These 
constructors are **MUCH** simpler than universal constructors, and they 
propagate parallel to one of the coordinate axes leaving a trail of duplicate
patterns at regular intervals.  Gosper's famous breeder is a simple example of
such a thing, but the generalization is easy, once you can make constructors 
with arbitrarily large spacing between patterns (I can show that this is 
possible).

The finite initial configuration of the CA is placed by hand, and the infinite
part is constructed at a rate faster than the propagation of logic in the CA.
Hence, the result simulates an infinite 1-D CA.

>It's not clear how to construct such control patterns in a direct way.  

Depending on how you define "clear," I guess.

>In
>general, two arbitrary patterns will not interact in a nice way, instead
>they'll make a mess.  But you could try a lot of possibilities for control and
>tape patterns, and reject the ones that produce undesirable interactions.  It
>seems that if you try enough, you may be able to come up with a small subset
>with only desirable interactions.  As far as i know, no one has done this, but
>i think it'd be a good area for Life hackers to explore.

I would distinguish two approaches.   The first is an "engineering" approach,  
in which we take all the small scale interactions that are already known (the
collection is quite robust).  We combine these in a structured way to get the
desired effect.  This is the approach I've taken above.  The second is a
"discovery" approach (which you've essentially outlined), in which we look for
small scale interactions that do exactly what we want.  

The disadvantage to the first approach is that the construction is quite
big.  On the other hand, we know "why" it works.  The disadvantage to the 
second approach is that the search may take an incredibly long time.  However,
the result will probably be much smaller than that of the former approach.  
I agree that it would be interesting to do a search for small CA cell 
simulators, and I don't know if anyone has worked on it.

One thing I've considered is turning Life into a 1-D CA by restricting one of 
its dimensions to k cells and wrapping the space cylindrically.  One 
interesting side effect is that gliders will propagate to adjacent cells.
A natural question is how big does k have to be before the CA is universal.
The construction of my previous posting shows k is finite.  On the other
hand, I doubt k is 1.  Has anybody worked on this?

--
Paul Callahan
callahan@cs.jhu.edu

From cellular-automata-request@Think.COM  Sat Mar 16 13:06:33 1991
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Date: 15 Mar 91 15:17:02 GMT
From: nsi91@parix.imag.fr (Pierre Bessiere)
Organization: IMAG Institute, University of Grenoble, France
Subject: Ecole de printemps NSI91
Message-Id: <19221@imag.imag.fr>
Newsgroups: comp.theory.cell-automata,comp.theory.dynamic-sys,comp.theory.self-org-sys,comp.ai.philosophy,comp.ai
Sender: ca-request@Think.COM
To: ca@Think.COM


                    Ecole de printemps

                          NSI 91

		     Derniere annonce

          Neurosciences et Sciences de l'Ingenieur

              Villars de Lans (Isere, FRANCE)
                   du 13 au 17 mai 1991
                                

Depuis 1982 ont lieu, toutes les annees paires, les journees "Neurosciences 
et Sciences de l'Ingenieur". Pluri-disciplinarite, francophonie et mobilite 
en ont ete les maitres mots depuis leur creation. Les 5emes journees ont 
eu lieu en 1990 a Aussois et ont remporte un vif succes. En 
consequence, deux decisions furent prises par les participants : creer 
une association NSI et organiser, les annees impaires, en alternance avec 
les journees, des cours dans les divers domaines concernes.

Nous sommes heureux de vous apprendre, d'une part, que l'association vient 
de voir le jour et, d'autre part, que sa premiere tache a ete 
l'organisation de l'ecole de printemps qui se tiendra en mai 1991 
a Villars de Lans.

La vocation de ce cours est triple :
-	permettre a des chercheurs confirmes d'approfondir leurs 
connaissances sur certaines disciplines connexes a la leur;
-	permettre a de jeunes chercheurs (etudiants en these) une 
initiation rapide aux sciences de la cognition;
-	enfin, permettre a des industriels l'acces a un panorama de 
certaines des recherches en cours.

Le cours aura une duree de 4 jours et demi (8 demi-journees de travail 
+ une demi-journee de detente). La duree de chaque session sera de 
4 heures : 3 heures d'expose + 1/2 heure de pause + 1/2 heure de discussion. 

                           PROGRAMME :
                          -------------

Lundi : 
-------
Theme de la journee :  rappels des notions fondamentales. 
Cette journee comporte deux sessions en parallele: les rappels des 
notions fondamentales de neurosciences destines aux ingenieurs et 
reciproquement, les rappels sur les reseaux de neurones formels 
destines aux specialistes des neurosciences.

9h30 -> 13h : 

LE NEURONE ET LA SYNAPSE
     P. Gogan 

RESEAUX DE NEURONES FORMELS SUPERVISES 
     F. Blayo

15h -> 19h :

STRUCTURES ANATOMIQUES DU SYSTEME NERVEUX 
     P. Mouchet

RESEAUX DE NEURONES FORMELS NON SUPERVISES 
     C. Jutten

Mardi : 
-------
Theme de la journee : Vision

9h -> 13h : SYSTEMES VISUELS BIOLOGIQUES 
     Y. Fregnac 

15h -> 19h : RESEAUX DE NEURONES ET RECONNAISSANCE DES FORMES 
     L. Personnaz

Mercredi : 
----------
Theme de la 1/2 journee : Applications industrielles

9h -> 13h : LES APPLICATIONS INDUSTRIELLES DES RESEAUX DE NEURONES 
Thomson ; C.E.A. ; Philips

Jeudi : 
-------
Theme de la journee : Methodes

9h -> 13h : METHODES EXPERIMENTALES POUR L'ETUDE DES RESEAUX 
DE NEURONES BIOLOGIQUES 
     Y. De Ribaupierre et F. Nagy 

15h -> 19h : METHODES MATHEMATIQUES POUR L'ETUDE DES 
RESEAUX DE NEURONES FORMELS 
     J. Demongeot

Vendredi :
----------
Theme de la 1/2 journee : Ouverture sur des disciplines connexes

9h -> 13h : INTELLIGENCE ARTIFICIELLE SYMBOLIQUE VERSUS 
CONNEXIONISME SUB-SYMBOLIQUE 
     B. Amy et C. Robert

Le mercredi apres-midi est reserve a la detente : activites sportives et 
touristiques seront proposees.

Un support de cours sera fourni a chaque personne inscrite.

En marge de ce cours, des "sessions posters" sont prevues, ainsi 
que des salons de discussion organises par themes. L'idee etant 
essentiellement de permettre aux etudiants en these, a qui ce cours 
est tout particulierement destine, de pouvoir 
exposer leurs idees (meme si elles n'ont pas une maturite suffisante 
pour etre publiees), et d'avoir l'opportunite de discuter de ces 
idees avec des chercheurs confirmes. D'autres supports que les posters, 
par exemple bandes videos ou demonstrations de logiciels, seront 
accueillis volontiers dans ce cadre dans la mesure des 
possibilites techniques.

Il est aussi envisage d'organiser, un soir, une conference - debat 
de nature plus philosophique. Sujet et intervenants restent 
a determiner.

Le programme du cours a ete compose sous l'egide d'un comite pedagogique 
de neuf membres representant les differentes disciplines concernees.

Comite pedagogique :
--------------------
J. Bullier, INSERM -U94-, Lyon
D. Collobert, CNET, Lannion
A. Germond, EPFL, Lausanne
J. Herault, TIRF/INPG/UJF, Grenoble
R. Pesti, ITMI, Grenoble
P. Puget, DLETI/CENG/CEA, Grenoble
J. de Ribaupierre, Inst. de physiologie, Lausanne
G. Tiberghien, Lab. de Psycho. Experimentale, Grenoble
F. Vallet, LCR/Thomson-CSF, Paris

L'organisation a, quant a elle, ete confiee aux personnes suivantes:

Comite d'organisation :
-----------------------
F. Berthommier, TIMB/IMAG, Grenoble
P. Bessiere, LGI/IMAG, Grenoble
P. Demartines, LAMI/EPFL, Lausanne
A. Guerin, TIRF/INPG, Grenoble

Site :
------

Villars de Lans est une magnifique petite ville de montagne situee au 
coeur du massif du Vercors a 35 kilometres de Grenoble.

Hebergement :
-------------

L'hebergement aura lieu a la residence de tourisme Le Grand Adret 
en chambre a deux lits, comprenant douche et WC. Les personnes 
souhaitant etre hebergees dans une chambre simple devront 
acquitter un supplement de 1000 FF. 

Repas :
-------

Les petits dejeuners seront pris a la residence d'acceuil, 
les dejeuners dans un restaurant pres de la salle de conference 
et les diners au choix dans l'un des nombreux restaurants de la 
ville, chaque participant recevant un ticket restaurant de 70 FF 
par diner. Attention : le diner de dimanche n'est pas prevu.

Tarifs :
--------

Les prix s'entendent tout compris : frais d'inscription a la conference, 
support de cours, cinq nuits d'hotel (a partir de dimanche soir), 
pension complete (du lundi matin  au vendredi midi). 

Paiement a l'ordre de : Agent Comptable INPG (NSI91)
                        ----------------------------

Toute inscription devra imperativement etre accompagnee d'un 
reglement ou d'un bon de commande pour pouvoir etre prise en compte.

Transport :
-----------

Une navette partira le dimanche soir a 21H de la gare routiere 
de Grenoble (a cote de la gare SNCF). Le prix de cette navette 
est compris dans les frais d'inscription, en revanche, tout 
autre mode de transport sera a la charge de la personne concernee.

Adhesion a l'association NSI :
------------------------------

La cotisation a l'association est de 100 FF. Tout adherent de 
l'association se voit octroyer une remise de 100 FF sur 
le tarif du cours.

L'adhesion a une association devant etre un acte volontaire, 
nous vous prions d'indiquer clairement votre desir d'adherer 
sur le formulaire d'inscription.


Adresse :
---------                            Ecole de printemps NSI91
                                     LGI / IMAG (P. Bessiere)
                                     BP53X
                                     38041 Grenoble Cedex
                                     FRANCE

                                     nsi91@parix.imag.fr
                                     Fax : (33)76.44.66.75.
                                     Telex : UJF 980 134 F


----------------------------------------------------------------------
                          INSCRIPTION A NSI91
                    (A envoyer a l'adresse ci dessus)

Nom :
Prenom :
Organisme ou societe :
Adresse :



Telephone :
Fax :
E-mail :

                          --------------------

              <15/01/91     <30/03/91     >15/03/91

Etudiant :        O             O             O (Cocher la case convenable)
                2000FF        2250FF        2500FF

Chercheur :       O             O             O
                2500FF        2750FF        3000FF

Industriel :      O             O             O
                3500FF        4000FF        4500FF

Supplement chambre individuelle :     O
                                    1000FF

                          ---------------------
                       ADHESION A L'ASSOCIATION NSI

Si vous voulez adherer ecrire en toutes lettres
"Je desire adherer a l'association NSI" et signer :




----------------------------------------------------------------------

From cellular-automata-request@Think.COM  Sat Mar 16 13:27:57 1991
Received: by mail.think.com; Sat, 16 Mar 91 09:06:53 -0500
Received: from Think.COM by mail.think.com; Sat, 16 Mar 91 09:06:51 -0500
Received: from bloom-beacon.MIT.EDU by Early-Bird.Think.COM; Sat, 16 Mar 91 09:06:47 EST
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	id AA16679; Sat, 16 Mar 91 08:43:54 EST
Received: from USENET by bloom-beacon.mit.edu with netnews
	for ca@think.com (ca@think.com)
	(contact usenet@bloom-beacon.mit.edu if you have questions)
Date: 16 Mar 91 01:10:14 GMT
From: jgk@osc.COM (Joe Keane)
Organization: Versant Object Technology, Menlo Park, CA
Subject: Re: How Intelligent are the Winning Ways?
Message-Id: <4671@osc.COM>
Newsgroups: comp.theory.cell-automata
References: <1991Mar5.171804.1429@zorch.SF-Bay.ORG>, <5717@acorn.co.uk>, <1991Mar12.155051.16488@zorch.SF-Bay.ORG>
Sender: ca-request@Think.COM
To: ca@Think.COM

A Turing Machine is just a special case of a one-dimenstional cellular
automaton.  We can consider a Turing machine to have tape states and control
states, where there is always exactly one instance of the latter.  The control
states and tape states can be added together or multiplied, it's not really
important.

How do we do this in Life?  We want the tape patterns to be something that
doesn't move around, for example configurations of blocks are fine.  We can
also use blinkers or something that flips between states because we probably
have constraints on what time we'll look at it.

We want the control patterns to be something which interacts with the tape
patterns in some predictable way.  An operation of the Turing machine consists
of a control pattern interacting with a neighboring tape pattern.  A new
control pattern is created where the tape pattern was, and a new tape pattern
is left where the control pattern was.

It's not clear how to construct such control patterns in a direct way.  In
general, two arbitrary patterns will not interact in a nice way, instead
they'll make a mess.  But you could try a lot of possibilities for control and
tape patterns, and reject the ones that produce undesirable interactions.  It
seems that if you try enough, you may be able to come up with a small subset
with only desirable interactions.  As far as i know, no one has done this, but
i think it'd be a good area for Life hackers to explore.

You may know that certain combinations of tape and control states can't occur
in your Turing machine.  You can take advantage of this to simplify the
construction of your control states.  Then if there's a programming error and
one of these forbidden combinations occurs, the machine may self-destruct.

With Life we have an additional advantage that it's two-dimensional.  So maybe
we can put the control states above the tape states.  I don't know if this
gains you anything, but it's fun to think about a big complicated control
spaceship flying over a long row of tape patterns.  The spaceship can fire
gliders or scout ships at the tape pattern and analyze what returns to decide
what to do next.

Note we don't really have to worry about constructing an arbitrary Turing
machine.  We only need to find a way to make one universal Turing machine.
This UTM could even have its program on a separate tape, given that we have a
lot of space.
--
Joe Keane, amateur mathematician

From cellular-automata-request@Think.COM  Sat Mar 16 17:17:07 1991
Received: by mail.think.com; Sat, 16 Mar 91 06:06:23 -0500
Received: from Think.COM by mail.think.com; Sat, 16 Mar 91 06:06:21 -0500
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	id AA10324; Sat, 16 Mar 91 05:49:03 EST
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	for ca@think.com (ca@think.com)
	(contact usenet@bloom-beacon.mit.edu if you have questions)
Date: 16 Mar 91 07:00:45 GMT
From: pattis@cs.washington.edu (Richard Pattis)
Organization: U of Washington, Computer Science, Seattle
Subject: PC Products: Fractals, Chaos, Cellular Automata
Message-Id: <15483@june.cs.washington.edu>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM

Is there any list (in a FAQ file) of available PC software concerning
Fractals, Chaos, and/or Cellular Automata.  For one example, I recall
a CA package by Rudy Rucker but have forgotton the details.

Rich Pattis

From cellular-automata-request@Think.COM  Sat Mar 16 17:27:19 1991
Received: by mail.think.com; Sat, 16 Mar 91 05:07:55 -0500
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	for ca@think.com (ca@think.com)
	(contact usenet@bloom-beacon.mit.edu if you have questions)
Date: 15 Mar 91 15:17:02 GMT
From: nsi91@parix.imag.fr (Pierre Bessiere)
Organization: IMAG Institute, University of Grenoble, France
Subject: Ecole de printemps NSI91
Message-Id: <19221@imag.imag.fr>
Newsgroups: comp.theory.cell-automata,comp.theory.dynamic-sys,comp.theory.self-org-sys,comp.ai.philosophy,comp.ai
Sender: ca-request@Think.COM
To: ca@Think.COM


                    Ecole de printemps

                          NSI 91

		     Derniere annonce

          Neurosciences et Sciences de l'Ingenieur

              Villars de Lans (Isere, FRANCE)
                   du 13 au 17 mai 1991
                                

Depuis 1982 ont lieu, toutes les annees paires, les journees "Neurosciences 
et Sciences de l'Ingenieur". Pluri-disciplinarite, francophonie et mobilite 
en ont ete les maitres mots depuis leur creation. Les 5emes journees ont 
eu lieu en 1990 a Aussois et ont remporte un vif succes. En 
consequence, deux decisions furent prises par les participants : creer 
une association NSI et organiser, les annees impaires, en alternance avec 
les journees, des cours dans les divers domaines concernes.

Nous sommes heureux de vous apprendre, d'une part, que l'association vient 
de voir le jour et, d'autre part, que sa premiere tache a ete 
l'organisation de l'ecole de printemps qui se tiendra en mai 1991 
a Villars de Lans.

La vocation de ce cours est triple :
-	permettre a des chercheurs confirmes d'approfondir leurs 
connaissances sur certaines disciplines connexes a la leur;
-	permettre a de jeunes chercheurs (etudiants en these) une 
initiation rapide aux sciences de la cognition;
-	enfin, permettre a des industriels l'acces a un panorama de 
certaines des recherches en cours.

Le cours aura une duree de 4 jours et demi (8 demi-journees de travail 
+ une demi-journee de detente). La duree de chaque session sera de 
4 heures : 3 heures d'expose + 1/2 heure de pause + 1/2 heure de discussion. 

                           PROGRAMME :
                          -------------

Lundi : 
-------
Theme de la journee :  rappels des notions fondamentales. 
Cette journee comporte deux sessions en parallele: les rappels des 
notions fondamentales de neurosciences destines aux ingenieurs et 
reciproquement, les rappels sur les reseaux de neurones formels 
destines aux specialistes des neurosciences.

9h30 -> 13h : 

LE NEURONE ET LA SYNAPSE
     P. Gogan 

RESEAUX DE NEURONES FORMELS SUPERVISES 
     F. Blayo

15h -> 19h :

STRUCTURES ANATOMIQUES DU SYSTEME NERVEUX 
     P. Mouchet

RESEAUX DE NEURONES FORMELS NON SUPERVISES 
     C. Jutten

Mardi : 
-------
Theme de la journee : Vision

9h -> 13h : SYSTEMES VISUELS BIOLOGIQUES 
     Y. Fregnac 

15h -> 19h : RESEAUX DE NEURONES ET RECONNAISSANCE DES FORMES 
     L. Personnaz

Mercredi : 
----------
Theme de la 1/2 journee : Applications industrielles

9h -> 13h : LES APPLICATIONS INDUSTRIELLES DES RESEAUX DE NEURONES 
Thomson ; C.E.A. ; Philips

Jeudi : 
-------
Theme de la journee : Methodes

9h -> 13h : METHODES EXPERIMENTALES POUR L'ETUDE DES RESEAUX 
DE NEURONES BIOLOGIQUES 
     Y. De Ribaupierre et F. Nagy 

15h -> 19h : METHODES MATHEMATIQUES POUR L'ETUDE DES 
RESEAUX DE NEURONES FORMELS 
     J. Demongeot

Vendredi :
----------
Theme de la 1/2 journee : Ouverture sur des disciplines connexes

9h -> 13h : INTELLIGENCE ARTIFICIELLE SYMBOLIQUE VERSUS 
CONNEXIONISME SUB-SYMBOLIQUE 
     B. Amy et C. Robert

Le mercredi apres-midi est reserve a la detente : activites sportives et 
touristiques seront proposees.

Un support de cours sera fourni a chaque personne inscrite.

En marge de ce cours, des "sessions posters" sont prevues, ainsi 
que des salons de discussion organises par themes. L'idee etant 
essentiellement de permettre aux etudiants en these, a qui ce cours 
est tout particulierement destine, de pouvoir 
exposer leurs idees (meme si elles n'ont pas une maturite suffisante 
pour etre publiees), et d'avoir l'opportunite de discuter de ces 
idees avec des chercheurs confirmes. D'autres supports que les posters, 
par exemple bandes videos ou demonstrations de logiciels, seront 
accueillis volontiers dans ce cadre dans la mesure des 
possibilites techniques.

Il est aussi envisage d'organiser, un soir, une conference - debat 
de nature plus philosophique. Sujet et intervenants restent 
a determiner.

Le programme du cours a ete compose sous l'egide d'un comite pedagogique 
de neuf membres representant les differentes disciplines concernees.

Comite pedagogique :
--------------------
J. Bullier, INSERM -U94-, Lyon
D. Collobert, CNET, Lannion
A. Germond, EPFL, Lausanne
J. Herault, TIRF/INPG/UJF, Grenoble
R. Pesti, ITMI, Grenoble
P. Puget, DLETI/CENG/CEA, Grenoble
J. de Ribaupierre, Inst. de physiologie, Lausanne
G. Tiberghien, Lab. de Psycho. Experimentale, Grenoble
F. Vallet, LCR/Thomson-CSF, Paris

L'organisation a, quant a elle, ete confiee aux personnes suivantes:

Comite d'organisation :
-----------------------
F. Berthommier, TIMB/IMAG, Grenoble
P. Bessiere, LGI/IMAG, Grenoble
P. Demartines, LAMI/EPFL, Lausanne
A. Guerin, TIRF/INPG, Grenoble

Site :
------

Villars de Lans est une magnifique petite ville de montagne situee au 
coeur du massif du Vercors a 35 kilometres de Grenoble.

Hebergement :
-------------

L'hebergement aura lieu a la residence de tourisme Le Grand Adret 
en chambre a deux lits, comprenant douche et WC. Les personnes 
souhaitant etre hebergees dans une chambre simple devront 
acquitter un supplement de 1000 FF. 

Repas :
-------

Les petits dejeuners seront pris a la residence d'acceuil, 
les dejeuners dans un restaurant pres de la salle de conference 
et les diners au choix dans l'un des nombreux restaurants de la 
ville, chaque participant recevant un ticket restaurant de 70 FF 
par diner. Attention : le diner de dimanche n'est pas prevu.

Tarifs :
--------

Les prix s'entendent tout compris : frais d'inscription a la conference, 
support de cours, cinq nuits d'hotel (a partir de dimanche soir), 
pension complete (du lundi matin  au vendredi midi). 

Paiement a l'ordre de : Agent Comptable INPG (NSI91)
                        ----------------------------

Toute inscription devra imperativement etre accompagnee d'un 
reglement ou d'un bon de commande pour pouvoir etre prise en compte.

Transport :
-----------

Une navette partira le dimanche soir a 21H de la gare routiere 
de Grenoble (a cote de la gare SNCF). Le prix de cette navette 
est compris dans les frais d'inscription, en revanche, tout 
autre mode de transport sera a la charge de la personne concernee.

Adhesion a l'association NSI :
------------------------------

La cotisation a l'association est de 100 FF. Tout adherent de 
l'association se voit octroyer une remise de 100 FF sur 
le tarif du cours.

L'adhesion a une association devant etre un acte volontaire, 
nous vous prions d'indiquer clairement votre desir d'adherer 
sur le formulaire d'inscription.


Adresse :
---------                            Ecole de printemps NSI91
                                     LGI / IMAG (P. Bessiere)
                                     BP53X
                                     38041 Grenoble Cedex
                                     FRANCE

                                     nsi91@parix.imag.fr
                                     Fax : (33)76.44.66.75.
                                     Telex : UJF 980 134 F


----------------------------------------------------------------------
                          INSCRIPTION A NSI91
                    (A envoyer a l'adresse ci dessus)

Nom :
Prenom :
Organisme ou societe :
Adresse :



Telephone :
Fax :
E-mail :

                          --------------------

              <15/01/91     <30/03/91     >15/03/91

Etudiant :        O             O             O (Cocher la case convenable)
                2000FF        2250FF        2500FF

Chercheur :       O             O             O
                2500FF        2750FF        3000FF

Industriel :      O             O             O
                3500FF        4000FF        4500FF

Supplement chambre individuelle :     O
                                    1000FF

                          ---------------------
                       ADHESION A L'ASSOCIATION NSI

Si vous voulez adherer ecrire en toutes lettres
"Je desire adherer a l'association NSI" et signer :




----------------------------------------------------------------------

From cellular-automata-request@Think.COM  Sat Mar 16 17:39:33 1991
Received: by mail.think.com; Sat, 16 Mar 91 09:06:53 -0500
Received: from Think.COM by mail.think.com; Sat, 16 Mar 91 09:06:51 -0500
Received: from bloom-beacon.MIT.EDU by Early-Bird.Think.COM; Sat, 16 Mar 91 09:06:47 EST
Received:  by bloom-beacon.MIT.EDU (5.61/25-eef)
	id AA16679; Sat, 16 Mar 91 08:43:54 EST
Received: from USENET by bloom-beacon.mit.edu with netnews
	for ca@think.com (ca@think.com)
	(contact usenet@bloom-beacon.mit.edu if you have questions)
Date: 16 Mar 91 01:10:14 GMT
From: jgk@osc.COM (Joe Keane)
Organization: Versant Object Technology, Menlo Park, CA
Subject: Re: How Intelligent are the Winning Ways?
Message-Id: <4671@osc.COM>
Newsgroups: comp.theory.cell-automata
References: <1991Mar5.171804.1429@zorch.SF-Bay.ORG>, <5717@acorn.co.uk>, <1991Mar12.155051.16488@zorch.SF-Bay.ORG>
Sender: ca-request@Think.COM
To: ca@Think.COM

A Turing Machine is just a special case of a one-dimenstional cellular
automaton.  We can consider a Turing machine to have tape states and control
states, where there is always exactly one instance of the latter.  The control
states and tape states can be added together or multiplied, it's not really
important.

How do we do this in Life?  We want the tape patterns to be something that
doesn't move around, for example configurations of blocks are fine.  We can
also use blinkers or something that flips between states because we probably
have constraints on what time we'll look at it.

We want the control patterns to be something which interacts with the tape
patterns in some predictable way.  An operation of the Turing machine consists
of a control pattern interacting with a neighboring tape pattern.  A new
control pattern is created where the tape pattern was, and a new tape pattern
is left where the control pattern was.

It's not clear how to construct such control patterns in a direct way.  In
general, two arbitrary patterns will not interact in a nice way, instead
they'll make a mess.  But you could try a lot of possibilities for control and
tape patterns, and reject the ones that produce undesirable interactions.  It
seems that if you try enough, you may be able to come up with a small subset
with only desirable interactions.  As far as i know, no one has done this, but
i think it'd be a good area for Life hackers to explore.

You may know that certain combinations of tape and control states can't occur
in your Turing machine.  You can take advantage of this to simplify the
construction of your control states.  Then if there's a programming error and
one of these forbidden combinations occurs, the machine may self-destruct.

With Life we have an additional advantage that it's two-dimensional.  So maybe
we can put the control states above the tape states.  I don't know if this
gains you anything, but it's fun to think about a big complicated control
spaceship flying over a long row of tape patterns.  The spaceship can fire
gliders or scout ships at the tape pattern and analyze what returns to decide
what to do next.

Note we don't really have to worry about constructing an arbitrary Turing
machine.  We only need to find a way to make one universal Turing machine.
This UTM could even have its program on a separate tape, given that we have a
lot of space.
--
Joe Keane, amateur mathematician

From cellular-automata-request@Think.COM  Sat Mar 16 17:42:38 1991
Received: by mail.think.com; Sat, 16 Mar 91 13:06:20 -0500
Received: from Think.COM by mail.think.com; Sat, 16 Mar 91 13:06:17 -0500
Received: from bloom-beacon.MIT.EDU by Early-Bird.Think.COM; Sat, 16 Mar 91 13:06:11 EST
Received:  by bloom-beacon.MIT.EDU (5.61/25-eef)
	id AA22025; Sat, 16 Mar 91 12:30:53 EST
Received: from USENET by bloom-beacon.mit.edu with netnews
	for ca@think.com (ca@think.com)
	(contact usenet@bloom-beacon.mit.edu if you have questions)
Date: 16 Mar 91 16:12:17 GMT
From: callahan@server.cs.jhu.edu (Paul Callahan)
Organization: JHU Computer Science Deparment, Baltimore MD
Subject: Re: How Intelligent are the Winning Ways?
Message-Id: <callahan.669140176@newton.cs.jhu.edu>
Newsgroups: comp.theory.cell-automata,sci.math
References: <5717@acorn.co.uk>, <1991Mar12.155051.16488@zorch.SF-Bay.ORG>, <4671@osc.COM>
Sender: ca-request@Think.COM
To: ca@Think.COM

In article <4671@osc.COM> jgk@osc.COM (Joe Keane) writes:
> [stuff about simulating a 1-D CA in Life]
>How do we do this in Life?  

Actually, I thought I did a passable job of explaining how several postings ago.
Basically, we know enough about Life to construct arbitrary finite state 
machines out of glider guns (usable as cells).  And it is possible to develop 
specific constructors for arbitrary collections of glider guns.  These 
constructors are **MUCH** simpler than universal constructors, and they 
propagate parallel to one of the coordinate axes leaving a trail of duplicate
patterns at regular intervals.  Gosper's famous breeder is a simple example of
such a thing, but the generalization is easy, once you can make constructors 
with arbitrarily large spacing between patterns (I can show that this is 
possible).

The finite initial configuration of the CA is placed by hand, and the infinite
part is constructed at a rate faster than the propagation of logic in the CA.
Hence, the result simulates an infinite 1-D CA.

>It's not clear how to construct such control patterns in a direct way.  

Depending on how you define "clear," I guess.

>In
>general, two arbitrary patterns will not interact in a nice way, instead
>they'll make a mess.  But you could try a lot of possibilities for control and
>tape patterns, and reject the ones that produce undesirable interactions.  It
>seems that if you try enough, you may be able to come up with a small subset
>with only desirable interactions.  As far as i know, no one has done this, but
>i think it'd be a good area for Life hackers to explore.

I would distinguish two approaches.   The first is an "engineering" approach,  
in which we take all the small scale interactions that are already known (the
collection is quite robust).  We combine these in a structured way to get the
desired effect.  This is the approach I've taken above.  The second is a
"discovery" approach (which you've essentially outlined), in which we look for
small scale interactions that do exactly what we want.  

The disadvantage to the first approach is that the construction is quite
big.  On the other hand, we know "why" it works.  The disadvantage to the 
second approach is that the search may take an incredibly long time.  However,
the result will probably be much smaller than that of the former approach.  
I agree that it would be interesting to do a search for small CA cell 
simulators, and I don't know if anyone has worked on it.

One thing I've considered is turning Life into a 1-D CA by restricting one of 
its dimensions to k cells and wrapping the space cylindrically.  One 
interesting side effect is that gliders will propagate to adjacent cells.
A natural question is how big does k have to be before the CA is universal.
The construction of my previous posting shows k is finite.  On the other
hand, I doubt k is 1.  Has anybody worked on this?

--
Paul Callahan
callahan@cs.jhu.edu

From cellular-automata-request@Think.COM  Mon Mar 18 08:20:39 1991
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Date: 18 Mar 91 06:57:55 GMT
From: ssingh@watserv1.waterloo.edu (Sneaky Sanj)
Organization: University of Waterloo
Subject: Re: PC Products: Fractals, Chaos, Cellular Automata
Message-Id: <1991Mar18.065755.18867@watserv1.waterloo.edu>
Newsgroups: comp.theory.cell-automata
References: <15483@june.cs.washington.edu>
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In article <15483@june.cs.washington.edu> pattis@cs.washington.edu (Richard Pattis) writes:
>Is there any list (in a FAQ file) of available PC software concerning
>Fractals, Chaos, and/or Cellular Automata.  For one example, I recall
>a CA package by Rudy Rucker but have forgotton the details.
>
>Rich Pattis


I don't think there exists a FAQ file. You should be able to get information
on Rudy Rucker's CA Lab by writing Autodesk, or perhaps someone from
Autodesk will contact you from the net.

Also look for James Gleick's chaos. It is also published by Autodesk, I
think.

Has anyone identified what particular properties a cellular automaton
rule must possess before it will yield fractal structures? Some will
and some won't.

Oh yes, if you want to explore fractals, fractint 15.1 will blow you
away. Hats off to Timothy Wegner et. al!!

Ice.

-- 
"No one had the guts... until now!"  
$anjay $ingh     Fire & "Ice"     ssingh@watserv1.[u]waterloo.{edu|cdn}/[ca]
ROBOTRON Hi-Score: 20 Million Points | A new level of (in)human throughput...
!blade_runner!terminator!terminator_II_judgement_day!watmath!watserv1!ssingh!

From cellular-automata-request@Think.COM  Mon Mar 18 11:02:42 1991
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Date: 18 Mar 91 06:57:55 GMT
From: ssingh@watserv1.waterloo.edu (Sneaky Sanj)
Organization: University of Waterloo
Subject: Re: PC Products: Fractals, Chaos, Cellular Automata
Message-Id: <1991Mar18.065755.18867@watserv1.waterloo.edu>
Newsgroups: comp.theory.cell-automata
References: <15483@june.cs.washington.edu>
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To: ca@Think.COM

In article <15483@june.cs.washington.edu> pattis@cs.washington.edu (Richard Pattis) writes:
>Is there any list (in a FAQ file) of available PC software concerning
>Fractals, Chaos, and/or Cellular Automata.  For one example, I recall
>a CA package by Rudy Rucker but have forgotton the details.
>
>Rich Pattis


I don't think there exists a FAQ file. You should be able to get information
on Rudy Rucker's CA Lab by writing Autodesk, or perhaps someone from
Autodesk will contact you from the net.

Also look for James Gleick's chaos. It is also published by Autodesk, I
think.

Has anyone identified what particular properties a cellular automaton
rule must possess before it will yield fractal structures? Some will
and some won't.

Oh yes, if you want to explore fractals, fractint 15.1 will blow you
away. Hats off to Timothy Wegner et. al!!

Ice.

-- 
"No one had the guts... until now!"  
$anjay $ingh     Fire & "Ice"     ssingh@watserv1.[u]waterloo.{edu|cdn}/[ca]
ROBOTRON Hi-Score: 20 Million Points | A new level of (in)human throughput...
!blade_runner!terminator!terminator_II_judgement_day!watmath!watserv1!ssingh!

From cellular-automata-request@Think.COM  Mon Mar 18 11:16:28 1991
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Date: 16 Mar 91 07:00:45 GMT
From: pattis@cs.washington.edu (Richard Pattis)
Organization: U of Washington, Computer Science, Seattle
Subject: PC Products: Fractals, Chaos, Cellular Automata
Message-Id: <15483@june.cs.washington.edu>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM

Is there any list (in a FAQ file) of available PC software concerning
Fractals, Chaos, and/or Cellular Automata.  For one example, I recall
a CA package by Rudy Rucker but have forgotton the details.

Rich Pattis

From cellular-automata-request@Think.COM  Mon Mar 18 11:32:07 1991
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Date: 15 Mar 91 15:17:02 GMT
From: nsi91@parix.imag.fr (Pierre Bessiere)
Organization: IMAG Institute, University of Grenoble, France
Subject: Ecole de printemps NSI91
Message-Id: <19221@imag.imag.fr>
Newsgroups: comp.theory.cell-automata,comp.theory.dynamic-sys,comp.theory.self-org-sys,comp.ai.philosophy,comp.ai
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                    Ecole de printemps

                          NSI 91

		     Derniere annonce

          Neurosciences et Sciences de l'Ingenieur

              Villars de Lans (Isere, FRANCE)
                   du 13 au 17 mai 1991
                                

Depuis 1982 ont lieu, toutes les annees paires, les journees "Neurosciences 
et Sciences de l'Ingenieur". Pluri-disciplinarite, francophonie et mobilite 
en ont ete les maitres mots depuis leur creation. Les 5emes journees ont 
eu lieu en 1990 a Aussois et ont remporte un vif succes. En 
consequence, deux decisions furent prises par les participants : creer 
une association NSI et organiser, les annees impaires, en alternance avec 
les journees, des cours dans les divers domaines concernes.

Nous sommes heureux de vous apprendre, d'une part, que l'association vient 
de voir le jour et, d'autre part, que sa premiere tache a ete 
l'organisation de l'ecole de printemps qui se tiendra en mai 1991 
a Villars de Lans.

La vocation de ce cours est triple :
-	permettre a des chercheurs confirmes d'approfondir leurs 
connaissances sur certaines disciplines connexes a la leur;
-	permettre a de jeunes chercheurs (etudiants en these) une 
initiation rapide aux sciences de la cognition;
-	enfin, permettre a des industriels l'acces a un panorama de 
certaines des recherches en cours.

Le cours aura une duree de 4 jours et demi (8 demi-journees de travail 
+ une demi-journee de detente). La duree de chaque session sera de 
4 heures : 3 heures d'expose + 1/2 heure de pause + 1/2 heure de discussion. 

                           PROGRAMME :
                          -------------

Lundi : 
-------
Theme de la journee :  rappels des notions fondamentales. 
Cette journee comporte deux sessions en parallele: les rappels des 
notions fondamentales de neurosciences destines aux ingenieurs et 
reciproquement, les rappels sur les reseaux de neurones formels 
destines aux specialistes des neurosciences.

9h30 -> 13h : 

LE NEURONE ET LA SYNAPSE
     P. Gogan 

RESEAUX DE NEURONES FORMELS SUPERVISES 
     F. Blayo

15h -> 19h :

STRUCTURES ANATOMIQUES DU SYSTEME NERVEUX 
     P. Mouchet

RESEAUX DE NEURONES FORMELS NON SUPERVISES 
     C. Jutten

Mardi : 
-------
Theme de la journee : Vision

9h -> 13h : SYSTEMES VISUELS BIOLOGIQUES 
     Y. Fregnac 

15h -> 19h : RESEAUX DE NEURONES ET RECONNAISSANCE DES FORMES 
     L. Personnaz

Mercredi : 
----------
Theme de la 1/2 journee : Applications industrielles

9h -> 13h : LES APPLICATIONS INDUSTRIELLES DES RESEAUX DE NEURONES 
Thomson ; C.E.A. ; Philips

Jeudi : 
-------
Theme de la journee : Methodes

9h -> 13h : METHODES EXPERIMENTALES POUR L'ETUDE DES RESEAUX 
DE NEURONES BIOLOGIQUES 
     Y. De Ribaupierre et F. Nagy 

15h -> 19h : METHODES MATHEMATIQUES POUR L'ETUDE DES 
RESEAUX DE NEURONES FORMELS 
     J. Demongeot

Vendredi :
----------
Theme de la 1/2 journee : Ouverture sur des disciplines connexes

9h -> 13h : INTELLIGENCE ARTIFICIELLE SYMBOLIQUE VERSUS 
CONNEXIONISME SUB-SYMBOLIQUE 
     B. Amy et C. Robert

Le mercredi apres-midi est reserve a la detente : activites sportives et 
touristiques seront proposees.

Un support de cours sera fourni a chaque personne inscrite.

En marge de ce cours, des "sessions posters" sont prevues, ainsi 
que des salons de discussion organises par themes. L'idee etant 
essentiellement de permettre aux etudiants en these, a qui ce cours 
est tout particulierement destine, de pouvoir 
exposer leurs idees (meme si elles n'ont pas une maturite suffisante 
pour etre publiees), et d'avoir l'opportunite de discuter de ces 
idees avec des chercheurs confirmes. D'autres supports que les posters, 
par exemple bandes videos ou demonstrations de logiciels, seront 
accueillis volontiers dans ce cadre dans la mesure des 
possibilites techniques.

Il est aussi envisage d'organiser, un soir, une conference - debat 
de nature plus philosophique. Sujet et intervenants restent 
a determiner.

Le programme du cours a ete compose sous l'egide d'un comite pedagogique 
de neuf membres representant les differentes disciplines concernees.

Comite pedagogique :
--------------------
J. Bullier, INSERM -U94-, Lyon
D. Collobert, CNET, Lannion
A. Germond, EPFL, Lausanne
J. Herault, TIRF/INPG/UJF, Grenoble
R. Pesti, ITMI, Grenoble
P. Puget, DLETI/CENG/CEA, Grenoble
J. de Ribaupierre, Inst. de physiologie, Lausanne
G. Tiberghien, Lab. de Psycho. Experimentale, Grenoble
F. Vallet, LCR/Thomson-CSF, Paris

L'organisation a, quant a elle, ete confiee aux personnes suivantes:

Comite d'organisation :
-----------------------
F. Berthommier, TIMB/IMAG, Grenoble
P. Bessiere, LGI/IMAG, Grenoble
P. Demartines, LAMI/EPFL, Lausanne
A. Guerin, TIRF/INPG, Grenoble

Site :
------

Villars de Lans est une magnifique petite ville de montagne situee au 
coeur du massif du Vercors a 35 kilometres de Grenoble.

Hebergement :
-------------

L'hebergement aura lieu a la residence de tourisme Le Grand Adret 
en chambre a deux lits, comprenant douche et WC. Les personnes 
souhaitant etre hebergees dans une chambre simple devront 
acquitter un supplement de 1000 FF. 

Repas :
-------

Les petits dejeuners seront pris a la residence d'acceuil, 
les dejeuners dans un restaurant pres de la salle de conference 
et les diners au choix dans l'un des nombreux restaurants de la 
ville, chaque participant recevant un ticket restaurant de 70 FF 
par diner. Attention : le diner de dimanche n'est pas prevu.

Tarifs :
--------

Les prix s'entendent tout compris : frais d'inscription a la conference, 
support de cours, cinq nuits d'hotel (a partir de dimanche soir), 
pension complete (du lundi matin  au vendredi midi). 

Paiement a l'ordre de : Agent Comptable INPG (NSI91)
                        ----------------------------

Toute inscription devra imperativement etre accompagnee d'un 
reglement ou d'un bon de commande pour pouvoir etre prise en compte.

Transport :
-----------

Une navette partira le dimanche soir a 21H de la gare routiere 
de Grenoble (a cote de la gare SNCF). Le prix de cette navette 
est compris dans les frais d'inscription, en revanche, tout 
autre mode de transport sera a la charge de la personne concernee.

Adhesion a l'association NSI :
------------------------------

La cotisation a l'association est de 100 FF. Tout adherent de 
l'association se voit octroyer une remise de 100 FF sur 
le tarif du cours.

L'adhesion a une association devant etre un acte volontaire, 
nous vous prions d'indiquer clairement votre desir d'adherer 
sur le formulaire d'inscription.


Adresse :
---------                            Ecole de printemps NSI91
                                     LGI / IMAG (P. Bessiere)
                                     BP53X
                                     38041 Grenoble Cedex
                                     FRANCE

                                     nsi91@parix.imag.fr
                                     Fax : (33)76.44.66.75.
                                     Telex : UJF 980 134 F


----------------------------------------------------------------------
                          INSCRIPTION A NSI91
                    (A envoyer a l'adresse ci dessus)

Nom :
Prenom :
Organisme ou societe :
Adresse :



Telephone :
Fax :
E-mail :

                          --------------------

              <15/01/91     <30/03/91     >15/03/91

Etudiant :        O             O             O (Cocher la case convenable)
                2000FF        2250FF        2500FF

Chercheur :       O             O             O
                2500FF        2750FF        3000FF

Industriel :      O             O             O
                3500FF        4000FF        4500FF

Supplement chambre individuelle :     O
                                    1000FF

                          ---------------------
                       ADHESION A L'ASSOCIATION NSI

Si vous voulez adherer ecrire en toutes lettres
"Je desire adherer a l'association NSI" et signer :




----------------------------------------------------------------------

From cellular-automata-request@Think.COM  Mon Mar 18 11:52:41 1991
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Date: 16 Mar 91 01:10:14 GMT
From: jgk@osc.COM (Joe Keane)
Organization: Versant Object Technology, Menlo Park, CA
Subject: Re: How Intelligent are the Winning Ways?
Message-Id: <4671@osc.COM>
Newsgroups: comp.theory.cell-automata
References: <1991Mar5.171804.1429@zorch.SF-Bay.ORG>, <5717@acorn.co.uk>, <1991Mar12.155051.16488@zorch.SF-Bay.ORG>
Sender: ca-request@Think.COM
To: ca@Think.COM

A Turing Machine is just a special case of a one-dimenstional cellular
automaton.  We can consider a Turing machine to have tape states and control
states, where there is always exactly one instance of the latter.  The control
states and tape states can be added together or multiplied, it's not really
important.

How do we do this in Life?  We want the tape patterns to be something that
doesn't move around, for example configurations of blocks are fine.  We can
also use blinkers or something that flips between states because we probably
have constraints on what time we'll look at it.

We want the control patterns to be something which interacts with the tape
patterns in some predictable way.  An operation of the Turing machine consists
of a control pattern interacting with a neighboring tape pattern.  A new
control pattern is created where the tape pattern was, and a new tape pattern
is left where the control pattern was.

It's not clear how to construct such control patterns in a direct way.  In
general, two arbitrary patterns will not interact in a nice way, instead
they'll make a mess.  But you could try a lot of possibilities for control and
tape patterns, and reject the ones that produce undesirable interactions.  It
seems that if you try enough, you may be able to come up with a small subset
with only desirable interactions.  As far as i know, no one has done this, but
i think it'd be a good area for Life hackers to explore.

You may know that certain combinations of tape and control states can't occur
in your Turing machine.  You can take advantage of this to simplify the
construction of your control states.  Then if there's a programming error and
one of these forbidden combinations occurs, the machine may self-destruct.

With Life we have an additional advantage that it's two-dimensional.  So maybe
we can put the control states above the tape states.  I don't know if this
gains you anything, but it's fun to think about a big complicated control
spaceship flying over a long row of tape patterns.  The spaceship can fire
gliders or scout ships at the tape pattern and analyze what returns to decide
what to do next.

Note we don't really have to worry about constructing an arbitrary Turing
machine.  We only need to find a way to make one universal Turing machine.
This UTM could even have its program on a separate tape, given that we have a
lot of space.
--
Joe Keane, amateur mathematician

From cellular-automata-request@Think.COM  Mon Mar 18 11:53:03 1991
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Date: 16 Mar 91 16:12:17 GMT
From: callahan@server.cs.jhu.edu (Paul Callahan)
Organization: JHU Computer Science Deparment, Baltimore MD
Subject: Re: How Intelligent are the Winning Ways?
Message-Id: <callahan.669140176@newton.cs.jhu.edu>
Newsgroups: comp.theory.cell-automata,sci.math
References: <5717@acorn.co.uk>, <1991Mar12.155051.16488@zorch.SF-Bay.ORG>, <4671@osc.COM>
Sender: ca-request@Think.COM
To: ca@Think.COM

In article <4671@osc.COM> jgk@osc.COM (Joe Keane) writes:
> [stuff about simulating a 1-D CA in Life]
>How do we do this in Life?  

Actually, I thought I did a passable job of explaining how several postings ago.
Basically, we know enough about Life to construct arbitrary finite state 
machines out of glider guns (usable as cells).  And it is possible to develop 
specific constructors for arbitrary collections of glider guns.  These 
constructors are **MUCH** simpler than universal constructors, and they 
propagate parallel to one of the coordinate axes leaving a trail of duplicate
patterns at regular intervals.  Gosper's famous breeder is a simple example of
such a thing, but the generalization is easy, once you can make constructors 
with arbitrarily large spacing between patterns (I can show that this is 
possible).

The finite initial configuration of the CA is placed by hand, and the infinite
part is constructed at a rate faster than the propagation of logic in the CA.
Hence, the result simulates an infinite 1-D CA.

>It's not clear how to construct such control patterns in a direct way.  

Depending on how you define "clear," I guess.

>In
>general, two arbitrary patterns will not interact in a nice way, instead
>they'll make a mess.  But you could try a lot of possibilities for control and
>tape patterns, and reject the ones that produce undesirable interactions.  It
>seems that if you try enough, you may be able to come up with a small subset
>with only desirable interactions.  As far as i know, no one has done this, but
>i think it'd be a good area for Life hackers to explore.

I would distinguish two approaches.   The first is an "engineering" approach,  
in which we take all the small scale interactions that are already known (the
collection is quite robust).  We combine these in a structured way to get the
desired effect.  This is the approach I've taken above.  The second is a
"discovery" approach (which you've essentially outlined), in which we look for
small scale interactions that do exactly what we want.  

The disadvantage to the first approach is that the construction is quite
big.  On the other hand, we know "why" it works.  The disadvantage to the 
second approach is that the search may take an incredibly long time.  However,
the result will probably be much smaller than that of the former approach.  
I agree that it would be interesting to do a search for small CA cell 
simulators, and I don't know if anyone has worked on it.

One thing I've considered is turning Life into a 1-D CA by restricting one of 
its dimensions to k cells and wrapping the space cylindrically.  One 
interesting side effect is that gliders will propagate to adjacent cells.
A natural question is how big does k have to be before the CA is universal.
The construction of my previous posting shows k is finite.  On the other
hand, I doubt k is 1.  Has anybody worked on this?

--
Paul Callahan
callahan@cs.jhu.edu

From cellular-automata-request@Think.COM  Mon Mar 18 12:41:56 1991
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Date: 16 Mar 91 07:00:45 GMT
From: pattis@cs.washington.edu (Richard Pattis)
Organization: U of Washington, Computer Science, Seattle
Subject: PC Products: Fractals, Chaos, Cellular Automata
Message-Id: <15483@june.cs.washington.edu>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM

Is there any list (in a FAQ file) of available PC software concerning
Fractals, Chaos, and/or Cellular Automata.  For one example, I recall
a CA package by Rudy Rucker but have forgotton the details.

Rich Pattis

From cellular-automata-request@Think.COM  Mon Mar 18 13:05:40 1991
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Date: 16 Mar 91 01:10:14 GMT
From: jgk@osc.COM (Joe Keane)
Organization: Versant Object Technology, Menlo Park, CA
Subject: Re: How Intelligent are the Winning Ways?
Message-Id: <4671@osc.COM>
Newsgroups: comp.theory.cell-automata
References: <1991Mar5.171804.1429@zorch.SF-Bay.ORG>, <5717@acorn.co.uk>, <1991Mar12.155051.16488@zorch.SF-Bay.ORG>
Sender: ca-request@Think.COM
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A Turing Machine is just a special case of a one-dimenstional cellular
automaton.  We can consider a Turing machine to have tape states and control
states, where there is always exactly one instance of the latter.  The control
states and tape states can be added together or multiplied, it's not really
important.

How do we do this in Life?  We want the tape patterns to be something that
doesn't move around, for example configurations of blocks are fine.  We can
also use blinkers or something that flips between states because we probably
have constraints on what time we'll look at it.

We want the control patterns to be something which interacts with the tape
patterns in some predictable way.  An operation of the Turing machine consists
of a control pattern interacting with a neighboring tape pattern.  A new
control pattern is created where the tape pattern was, and a new tape pattern
is left where the control pattern was.

It's not clear how to construct such control patterns in a direct way.  In
general, two arbitrary patterns will not interact in a nice way, instead
they'll make a mess.  But you could try a lot of possibilities for control and
tape patterns, and reject the ones that produce undesirable interactions.  It
seems that if you try enough, you may be able to come up with a small subset
with only desirable interactions.  As far as i know, no one has done this, but
i think it'd be a good area for Life hackers to explore.

You may know that certain combinations of tape and control states can't occur
in your Turing machine.  You can take advantage of this to simplify the
construction of your control states.  Then if there's a programming error and
one of these forbidden combinations occurs, the machine may self-destruct.

With Life we have an additional advantage that it's two-dimensional.  So maybe
we can put the control states above the tape states.  I don't know if this
gains you anything, but it's fun to think about a big complicated control
spaceship flying over a long row of tape patterns.  The spaceship can fire
gliders or scout ships at the tape pattern and analyze what returns to decide
what to do next.

Note we don't really have to worry about constructing an arbitrary Turing
machine.  We only need to find a way to make one universal Turing machine.
This UTM could even have its program on a separate tape, given that we have a
lot of space.
--
Joe Keane, amateur mathematician

From cellular-automata-request@Think.COM  Mon Mar 18 13:06:03 1991
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Date: 16 Mar 91 16:12:17 GMT
From: callahan@server.cs.jhu.edu (Paul Callahan)
Organization: JHU Computer Science Deparment, Baltimore MD
Subject: Re: How Intelligent are the Winning Ways?
Message-Id: <callahan.669140176@newton.cs.jhu.edu>
Newsgroups: comp.theory.cell-automata,sci.math
References: <5717@acorn.co.uk>, <1991Mar12.155051.16488@zorch.SF-Bay.ORG>, <4671@osc.COM>
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In article <4671@osc.COM> jgk@osc.COM (Joe Keane) writes:
> [stuff about simulating a 1-D CA in Life]
>How do we do this in Life?  

Actually, I thought I did a passable job of explaining how several postings ago.
Basically, we know enough about Life to construct arbitrary finite state 
machines out of glider guns (usable as cells).  And it is possible to develop 
specific constructors for arbitrary collections of glider guns.  These 
constructors are **MUCH** simpler than universal constructors, and they 
propagate parallel to one of the coordinate axes leaving a trail of duplicate
patterns at regular intervals.  Gosper's famous breeder is a simple example of
such a thing, but the generalization is easy, once you can make constructors 
with arbitrarily large spacing between patterns (I can show that this is 
possible).

The finite initial configuration of the CA is placed by hand, and the infinite
part is constructed at a rate faster than the propagation of logic in the CA.
Hence, the result simulates an infinite 1-D CA.

>It's not clear how to construct such control patterns in a direct way.  

Depending on how you define "clear," I guess.

>In
>general, two arbitrary patterns will not interact in a nice way, instead
>they'll make a mess.  But you could try a lot of possibilities for control and
>tape patterns, and reject the ones that produce undesirable interactions.  It
>seems that if you try enough, you may be able to come up with a small subset
>with only desirable interactions.  As far as i know, no one has done this, but
>i think it'd be a good area for Life hackers to explore.

I would distinguish two approaches.   The first is an "engineering" approach,  
in which we take all the small scale interactions that are already known (the
collection is quite robust).  We combine these in a structured way to get the
desired effect.  This is the approach I've taken above.  The second is a
"discovery" approach (which you've essentially outlined), in which we look for
small scale interactions that do exactly what we want.  

The disadvantage to the first approach is that the construction is quite
big.  On the other hand, we know "why" it works.  The disadvantage to the 
second approach is that the search may take an incredibly long time.  However,
the result will probably be much smaller than that of the former approach.  
I agree that it would be interesting to do a search for small CA cell 
simulators, and I don't know if anyone has worked on it.

One thing I've considered is turning Life into a 1-D CA by restricting one of 
its dimensions to k cells and wrapping the space cylindrically.  One 
interesting side effect is that gliders will propagate to adjacent cells.
A natural question is how big does k have to be before the CA is universal.
The construction of my previous posting shows k is finite.  On the other
hand, I doubt k is 1.  Has anybody worked on this?

--
Paul Callahan
callahan@cs.jhu.edu

From cellular-automata-request@Think.COM  Mon Mar 18 14:04:04 1991
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Date: 16 Mar 91 07:00:45 GMT
From: pattis@cs.washington.edu (Richard Pattis)
Organization: U of Washington, Computer Science, Seattle
Subject: PC Products: Fractals, Chaos, Cellular Automata
Message-Id: <15483@june.cs.washington.edu>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
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Is there any list (in a FAQ file) of available PC software concerning
Fractals, Chaos, and/or Cellular Automata.  For one example, I recall
a CA package by Rudy Rucker but have forgotton the details.

Rich Pattis

From cellular-automata-request@Think.COM  Mon Mar 18 14:08:00 1991
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Date: 18 Mar 91 16:55:06 GMT
From: burton@unixg.ubc.ca (Steve Cumming, net.leftist)
Organization: University of British Columbia, Vancouver, B.C., Canada
Subject: CA in hardware
Message-Id: <1991Mar18.165506.15135@unixg.ubc.ca>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
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In "Cellular Automata Machines", Margoulis and I can't recall who,
1985, a hardware implementation of a CAM for PC's, based on FORTH
is described. It is claimed that the thing is available from
an outfit called "Systems Concepts" in San Francisco.

I can't track them down. Has anyone out there more up to date
info?

I want one of these to test out some ideas about integrating
simulation models of ecological processes with GIS....

Steve C.



--
#include "../h/disclaimer.h"        /* I am not really Phil Burton, btw. */
burton@unixg.ubc.ca		    ... and if dinosaurs "became" birds	
Steve Cumming, a.k.a.			what will we become?   - Anselm Hollow.
			

From cellular-automata-request@Think.COM  Mon Mar 18 15:02:24 1991
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Date: 16 Mar 91 07:00:45 GMT
From: pattis@cs.washington.edu (Richard Pattis)
Organization: U of Washington, Computer Science, Seattle
Subject: PC Products: Fractals, Chaos, Cellular Automata
Message-Id: <15483@june.cs.washington.edu>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM

Is there any list (in a FAQ file) of available PC software concerning
Fractals, Chaos, and/or Cellular Automata.  For one example, I recall
a CA package by Rudy Rucker but have forgotton the details.

Rich Pattis

From cellular-automata-request@Think.COM  Mon Mar 18 15:20:38 1991
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Date: 18 Mar 91 16:55:06 GMT
From: burton@unixg.ubc.ca (Steve Cumming, net.leftist)
Organization: University of British Columbia, Vancouver, B.C., Canada
Subject: CA in hardware
Message-Id: <1991Mar18.165506.15135@unixg.ubc.ca>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM

In "Cellular Automata Machines", Margoulis and I can't recall who,
1985, a hardware implementation of a CAM for PC's, based on FORTH
is described. It is claimed that the thing is available from
an outfit called "Systems Concepts" in San Francisco.

I can't track them down. Has anyone out there more up to date
info?

I want one of these to test out some ideas about integrating
simulation models of ecological processes with GIS....

Steve C.



--
#include "../h/disclaimer.h"        /* I am not really Phil Burton, btw. */
burton@unixg.ubc.ca		    ... and if dinosaurs "became" birds	
Steve Cumming, a.k.a.			what will we become?   - Anselm Hollow.
			

From cellular-automata-request@Think.COM  Tue Mar 19 10:48:38 1991
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Date: 19 Mar 91 14:14:11 GMT
From: ray@brahms.udel.edu (Thomas Ray)
Organization: University of Delaware
Subject: Synthetic Life followup: Artificial Life mailing list
Message-Id: <19774@brahms.udel.edu>
Newsgroups: comp.ai,comp.ai.edu,comp.ai.neural-nets,comp.theory,comp.theory.cell-automata,comp.theory.dynamic-sys,comp.theory.self-org-sys
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     In my original posting on Synthetic Life, I forgot to mention that
there is an Artificial Life mailing list.  It is distributed as a digest
to avoid chaos.  You may subscribe to the list by sending a message to:

alife-request@iuvax.cs.indiana.edu

and you may post to the list by sending a message to:

alife@iuvax.cs.indiana.edu

                             Tom Ray
                       University of Delaware
                  School of Life & Health Sciences
                      Newark, Delaware  19716
                        ray@brahms.udel.edu
                         302-451-2281 (FAX)
                            302-451-2753

From cellular-automata-request@Think.COM  Mon Mar 25 18:50:39 1991
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Date: 25 Mar 91 19:56:41 GMT
From: callahan@server.cs.jhu.edu (Paul Callahan)
Organization: JHU Computer Science Deparment, Baltimore MD
Subject: Re: Xlife 3.0
Message-Id: <callahan.669931123@newton.cs.jhu.edu>
Newsgroups: comp.theory.cell-automata,comp.windows.x
References: <wbvK9dO00awJ8ClYJc@andrew.cmu.edu>
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In article <wbvK9dO00awJ8ClYJc@andrew.cmu.edu> jb7m+@andrew.cmu.edu (Jon C. R. Bennett) writes:
> [ about the new release of Xlife ]

I wrote most of the user interface and file loading extensions very recently,
and there may still be some bugs or inconsistencies with the last release.
I tried to cater the new stuff to careful life tinkering as opposed to just
loading and watching.  I'm very interested in making the interface as usable
as possible, so I'd like comments and bug reports.  Assuming I have time, I'll 
try to track down these bugs (or convince you that they're features :-).  

I just found a bug when trying load files in absolute format.  It comes up
if you've moved the view before loading.  Basically, it's an inconsistency 
between new code and old.  I suspect most of the bugs will be of this nature.
The fix is as follows:

Go to the statement at line 497 in file.c:

     addcell(xpos + ...,
              ypos + ... )

This should be changed to

     addcell((xpos-loadx)+STARTPOS + ...,
              (ypos-loady)+STARTPOS + ... )

This will cause absolute mode patterns to be loaded in the upper left corner
of the displayed area.  Without this fix, the pattern appears at some bizarre
location that is not displayed.  

To get around the problem without fixing the source, you have two choices. 

(a) don't use absolute mode (i.e. recite the mantra "absolute == obsolete" 
until you feel enlightenment coming upon you).  This will also mean appending 
"#R" to the beginning of all non-picture files produced by 'S'.

(b) First do 'I' on loaded file, and use the center-of-mass command ('5') to
put the pattern in view.

I thought I did reasonable testing on Xlife, but it was mainly with respect
to the features I use.  I don't use absolute mode, and I don't use 'S' on
patterns too big to save as pictures (which is why I added the include 
extensions).  I don't want to make Xlife harder to use for people who do
use these things, so please report any anomalies and I'll try to fix them.

--
Paul Callahan
callahan@cs.jhu.edu

From cellular-automata-request@Think.COM  Fri Mar 29 09:46:26 1991
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Date: Thu, 28 Mar 91 14:45 PST
From: Bill Gosper <rwg@RUSSIAN.SPA.Symbolics.COM>
Subject: Re: on Life (and Death)
To: ACW@RUSSIAN.SPA.Symbolics.COM
Cc: "aipdc@castle.edinburgh.ac.uk"@ELEPHANT-BUTTE.SCRC.Symbolics.COM,
        "drhickerson@ucdavis.edu"@ELEPHANT-BUTTE.SCRC.Symbolics.COM,
        "CA@Think.COM"@ELEPHANT-BUTTE.SCRC.Symbolics.COM
In-Reply-To: <19910328162012.4.ACW@PALLANDO.SCRC.Symbolics.COM>
Message-Id: <19910328224539.9.RWG@TSUNAMI.SPA.Symbolics.COM>

I've forwarded this to rcs@la.tis.com.

    Date: Thu, 28 Mar 1991 11:20-0500
    From: Allan C. Wechsler <ACW@YUKON.SCRC.Symbolics.COM>

	Date: Wed, 27 Mar 1991 12:51 EST
	From: Paul Crowley <aipdc@castle.edinburgh.ac.uk>

	What's the simplest known pattern that has no parent?

    Winning Ways p. 829 gives:

    xxxxxxxxxxxxxx xxxxxxxxxxxxxxxxxx
    x x x x x x xxxx xx xxx xxx xx xx
    xxxxxxxxxxxxx x x xxx xxx xxx xx
    x x x x x x xx xxxxx xxx xxx xxxx
     x x x x x x xxx x xxx xxx xx x x
    xxxxxxxxxxxxxx xxxx xxx xxx xxxxx
     x x x x x x xxx xxxx xxx xxx x x
    x x x x x x x x x xx xxx xxx x xx
    xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

    I understand Schroeppel was in the group that discovered this; I don't
    know his net address but I've CC'd Gosper and perhaps he'd be willing to
    forward to Schroeppel our request to hear the story of this monster's
    discovery.

I think Roger Banks wrote the "ataviser" program, and some subset of Banks,
Schroeppel, Mike Speciner, and Mike Beeler "manually" guided a marathon
tree search.

About a year and a half ago, Schroeppel and Hickerson found a bunch of
patterns with very small predecessor counts.  These are used as modules
in existence proofs for GOE's within various rectangles, some quite cozy.
Rich should know the current record.

From cellular-automata-request@Think.COM  Thu May  2 09:19:52 1991
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X-Comment: From: vigyan!uucp  - Header Corrected at shakti.ncst.ernet.in

Does anybody know of any e-mailing list on fractals and/or dynamical
systems?  If you know, please let me know the contact e-mail
address(es).  Also, if there are any public domain software (for PC/AT
or UNIX, say SUN) for experimenting with fractals and/or dynamical
systems, or for designing fractal images, I would like to hear about
them and the contact addresses.

Thanks a lot.

Chandan Haldar                 | Internet:
Doctoral Student               |    csa!chandan@vigyan.ernet.in
Department of Computer Science |    csa%chandan@vigyan.ernet.in
	and Automation         | UUCP:
Indian Institute of Science    | ...uunet!shakti!vigyan!csa!chandan
Bangalore 560 012  INDIA       | Phone:  (91) 0812-344411  x2368      

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From cellular-automata-request@Think.COM  Mon Jun  3 18:35:19 1991
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Date: 3 Jun 91 21:26:30 GMT
From: dhansen@nmsu.edu (Deren Hansen)
Organization: Computing Research Lab
Subject: Information about the CAM boards
Message-Id: <DHANSEN.91Jun3152630@haywire.nmsu.edu>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM

While I know the subject was recently discussed, I didn't need the
information then, but I do now.  Would someone be good enough to
post or email me information about the CAM-8 pc board?
In particular, what company is producing the boards, what are the
general specifications of the boards, and does anyone have any
experience with the latest boards?

Thanks.
 

From singer@Think.COM  Mon Jul  8 10:03:29 1991
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Date: Mon, 8 Jul 91 10:03:28 EDT
Message-Id: <9107081403.AA15678@godot.think.com>
To: cellular-automata@Think.COM
Subject: Best speed

What is the best speed (millions of updates a second) that people get on
CA's?  How about if we restrict it to hexagonal grids?  I know there are a
lot of details needed to make sense of any time you provide me, but this is
just to get a rough feel for what is possible -- I'll look into the details
later.

Alex

From tamayo@Think.COM  Mon Jul  8 14:18:04 1991
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To: singer@Think.COM
Cc: cellular-automata@Think.COM
In-Reply-To: alexander singer's message of Mon, 8 Jul 91 10:03:28 EDT <9107081403.AA15678@godot.think.com>
Subject: Aprox. speed of a CM-2 CA


   If you allow for the possibility of bit packing and consider simple
boolean rules, which require about 15 instructions, my guess is that the
peak speed of a 64k CM-2 should be about 20-40 Giga-updates/second.

-Pablo





       

From cellular-automata-request@Think.COM  Thu Jul 11 04:25:32 1991
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Date: 1 Jul 91 14:48:27 GMT
From: rak@crosfield.co.uk (Richard Kirk)
Organization: Crosfield Electronics, Hemel Hempstead, United Kingdom.
Subject: Re: Zhabotinsky reacion simualtion.
Message-Id: <10484@suns3.crosfield.co.uk>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM

Toffoli & Margolus describe an algorithm for simulating `tube-worms' where
one cell on stimulation withdraws into a dormant state, counts to three, then 
re-emerges. There are some pictures of what the results should look like on
page 84 of their book.

I tried to re-do their experiment on a different machine but it didn't give
me the same nice spiral patterns. has anyone else tried this?

-- 
Richard Kirk    Image Processing Dept     Crosfield Electronics Ltd. U.K.
                0442-230000 x3361/3591    Hemel Hempstead, Herts, HP2 7RH

From cellular-automata-request@Think.COM  Sat Jul 13 15:21:35 1991
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Date: Mon, 8 Jul 91 16:17:30 GMT
From: francis@hanauma.stanford.edu (Francis Muir)
Organization: Stanford University, Department of Geophysics
Subject: Re: Best speed
Message-Id: <1991Jul8.161730.19020@leland.Stanford.EDU>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
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Alex Singer writes:

  What is the best speed (millions of updates a second) that people get on
  CA's?  How about if we restrict it to hexagonal grids?  

How about if we don't restrict it to hexagonal grids? If we are talking
about real problems in Physics, then we can no longer afford to cripple
ourselves by constraining ourselves to living in Flatland. 

						Fido

francis@hanauna.stanford .edu, where space is 4-dimensional...

From cellular-automata-request@Think.COM  Sat Jul 13 17:21:14 1991
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Date: 8 Jul 91 18:52:49 GMT
From: dab@ubitrex.mb.ca (Danny Boulet)
Organization: Ubitrex Corporation, Winnipeg, Manitoba, Canada
Subject: Re: Best speed
Message-Id: <1991Jul8.185249.1969@ccu.umanitoba.ca>
Newsgroups: comp.theory.cell-automata
References: <9107081403.AA15678@godot.think.com>
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In article <9107081403.AA15678@godot.think.com> singer@Think.COM (alexander singer) writes:
>What is the best speed (millions of updates a second) that people get on
>CA's?  How about if we restrict it to hexagonal grids?  I know there are a
>lot of details needed to make sense of any time you provide me, but this is
>just to get a rough feel for what is possible -- I'll look into the details
>later.
>
>Alex

I seem to recall reading about a cellular automata running on a Cray doing
something in the hundreds of millions of cell updates per second.  It was a
CA modelling fluid flow using a 2-D hexagonal grid.

If you need the reference or more details, let me know and I'll try to find it
(it's at home and I'm at work right now).

From cellular-automata-request@Think.COM  Sat Jul 13 21:21:48 1991
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Date: 5 Jul 91 11:03:52 GMT
From: rak@crosfield.co.uk (Richard Kirk)
Organization: Crosfield Electronics, Hemel Hempstead, United Kingdom.
Subject: Re: Automata programs for the AT?
Message-Id: <10538@suns3.crosfield.co.uk>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM

Is there any good software for cellular automata on a 386?

I recently bought Sintar Software's CellMaster package. It was cheap and 
served as an introduction. It has a generous neighbourhood of 2 bits for a
3x3 area. I now want to try and use the automata for cleaning up images and 
text. To do this I want to be able to diffuse particles (text elements) 
conservatively. To do this as Toffoli and Margolus do would require a whole
plane to generate the pseudorandom numbers, another plane to handshake the
swapping of cells, and so on.

I have gone out on a bit of a limb in mucking about with these things in the 
first place: I haven't the time to write a full blown simulation unless I can
prove they can do something really useful for us.

P.S. Where is everybody? Is there a new newsgroup, or what?

-- 
Richard Kirk         Image Processing Group    Crosfield Electronics Ltd. U.K.
rak@crosfield.co.uk  0442-230000 x3361/3591    Hemel Hempstead, Herts, HP2 7RH

From cellular-automata-request@Think.COM  Sat Jul 13 22:19:59 1991
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Date: 8 Jul 91 19:56:03 GMT
From: owen@Autodesk.COM (Owen Rowley)
Subject: Re: Automata programs for the AT?
Message-Id: <6251@autodesk.COM>
Newsgroups: comp.theory.cell-automata
References: <10538@suns3.crosfield.co.uk>
Sender: ca-request@Think.COM
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In article <10538@suns3.crosfield.co.uk>, rak@crosfield.co.uk (Richard Kirk) writes:
> Is there any good software for cellular automata on a 386?
> 
> I recently bought Sintar Software's CellMaster package. It was cheap and 
> served as an introduction. It has a generous neighbourhood of 2 bits for a
> 3x3 area. I now want to try and use the automata for cleaning up images and 
> text. To do this I want to be able to diffuse particles (text elements) 
> conservatively. To do this as Toffoli and Margolus do would require a whole
> plane to generate the pseudorandom numbers, another plane to handshake the
> swapping of cells, and so on.

Autodesk has two products which you might find interesting.


CA-Lab is a package with several cellular automata programs.
The principle authors were Rudy Rucker and John Walker.
I think that CA-Lab sells for $59.95 retail.

Chaos the software,  has six modules , one of which is a cellular automata
module.  Chaos the Software is designed to be a companion to "Chaos" the
book by James Gleick.  Again, Rudy Rucker , was a programmer for this
package.
Chaos the software sells for $59.95 and requires a VGA display capability.

Both packages run quite nicely on a 386 machine.

The CA lab product is probably the one you want, but both are
outstanding products.  IMNSHO :-)

If your local Software emporiums do not carry these products, you
can call 1-800-688-2344 , while you're at it you might pass that number off
to your local Software outlets , so they can get in on the fun too :-)

You can order these products to be charged via your VISA or Mastercard
from the 800 number I've given above.
They will be shipped to you directly.



LUX .. owen
--
|D. Owen Rowley, {uunet,fernwood,sun}!autodesk!owen , { owen@autodesk.com }|
| "All sufficiently advanced analysis must eventually abandon Aristotelian |
| certitude and accept models -reality tunnels- based on probabilities"    |
|             Robert Anton Wilson, " QUANTUM PSYCHOLOGY "                  | 

From cellular-automata-request@Think.COM  Sun Jul 14 10:22:20 1991
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Date: 10 Jul 91 13:35:36 GMT
From: maf@cs.ed.ac.uk (Matt Fairtlough)
Organization: Department of Computer Science, University of Edinburgh
Subject: Automata programs for a Sun4
Message-Id: <14083@skye.cs.ed.ac.uk>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM

Is there any good software for cellular automata on Sun4's (running Unix with X-windows)?  We have a life program installed locally, but it is very limited (rules cannot be changed, files cannot be saved or sensibly edited, etc.).  Thanks in anticipation for any replies.

p.s. this is my first posting to the net, so please excuse defects!

-- 
Matt Fairtlough					maf@cs.ed.ac.uk
LFCS, Department of Computer Science			
Room 2615, JCMB, King's Buildings, Edinburgh	031-650-5152

From cellular-automata-request@Think.COM  Mon Jul 15 23:20:30 1991
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Date: 9 Jul 91 04:57:29 GMT
From: emwq@tartarus.uchicago.edu (erik winfree)
Organization: University of Chicago
Subject: Re: Zhabotinsky reacion simualtion.
Message-Id: <emwq.679035449@tartarus.uchicago.edu>
Newsgroups: comp.theory.cell-automata
References: <10484@suns3.crosfield.co.uk>
Sender: ca-request@Think.COM
To: ca@Think.COM


In <10484@suns3.crosfield.co.uk> rak@crosfield.co.uk (Richard Kirk) writes:

>Toffoli & Margolus describe an algorithm for simulating `tube-worms' where
>one cell on stimulation withdraws into a dormant state, counts to three, then 
>re-emerges. There are some pictures of what the results should look like on
>page 84 of their book.

>I tried to re-do their experiment on a different machine but it didn't give
>me the same nice spiral patterns. has anyone else tried this?

>-- 
>Richard Kirk    Image Processing Dept     Crosfield Electronics Ltd. U.K.
>                0442-230000 x3361/3591    Hemel Hempstead, Herts, HP2 7RH

I've done the Zhabotinsky reaction simulations.  Once you get the rules
right, there's no way you won't get spirals (given the proper initial
conditions). For simplicity, let's consider a 3-state CA, with states
Q=quiescent, A=active, R=refractory.  Cells in state A goes to state R
no matter what; cells in state R go to state Q no matter what; cells in
state Q stay in state Q *unless* there is a neighboring cell in state A
(you can use a four cell or eight cell neighborhood, your choice).  It is
important that all cells get updated *simultaneously* -- i.e. you should
keep two arrays of state, and write from one to the other. As for initial
conditions, a single active cell should produce a single expanding wave
(which should die when it hits the edges or when it collides with itself, if
you use wrapped boundary conditions), while a line of active cells immediately
adjacent to a line of quiescent cells will produce two counter-rotating
spirals:

		AAAAAAAAAAAA
		QQQQQQQQQQQQ


Once you have that working, how to code simulations with more states
should become clear.  It is done by inserting more active states and more
quiescent states into the life cycle of a cell; you just be sure to
satisfy some ratio of number to active states to number of quiescent
states (exactly what it is I forget).  Good luck.

Erik Winfree
emwq@tartarus.uchicago.edu

From cellular-automata-request@Think.COM  Tue Jul 16 18:01:59 1991
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Date: Tue, 16 Jul 91 16:01:46 MDT
From: cgl@t13.Lanl.GOV (Chris Langton)
Message-Id: <9107162201.AA01909@t13.lanl.gov>
To: ca@Think.COM
Subject: Re: Zhabotinsky reacion simualtion.

Richard Kirk writes:

>    Toffoli & Margolus describe an algorithm for simulating `tube-worms' where
> one cell on stimulation withdraws into a dormant state, counts to three, then 
> re-emerges. There are some pictures of what the results should look like on
> page 84 of their book.
> 
> I tried to re-do their experiment on a different machine but it didn't give
> me the same nice spiral patterns. has anyone else tried this?


  I have reproduced this basic phenomenon in many different systems on many
different machines. Their rule belongs to a general class of rules defining 
"excitable media", in which there is an "excitable" state which, under
some threshold function of excitation in its neighborhood, becomes an
"excited" state, and then relaxes through an unexcitable "refractory" state
(or a series of them) to the "excitable" state again. Spiral waves are
generic to this class of rules, so if you do not observe them, I would 
be surprised if you don't either have a bizzare threshold function for 
excitation or a bug in your code.

   Cheers!

   Chris Langton

   Complex Systems Group
   MS B213, Theoretical Division	Phone: (505) 667-9471
   Los Alamos National Laboratory	Email: cgl@t13.lanl.gov
   Los Alamos, New Mexico, USA		FAX:   (505) 665-3003
   87545



   


From cellular-automata-request@Think.COM  Wed Jul 17 02:22:58 1991
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Date: 6 Jul 91 03:25:44 GMT
From: dbk@odgate.odesta.com (Dan Keith)
Organization: Emergent Systems
Subject: Re: Automata programs for the AT?
Message-Id: <1991Jul6.032544.3949@odgate.odesta.com>
Newsgroups: comp.theory.cell-automata
References: <10538@suns3.crosfield.co.uk>
Sender: ca-request@Think.COM
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rak@crosfield.co.uk (Richard Kirk) writes:

>Is there any good software for cellular automata on a 386?

There's a product called CALab distributed by Autodesk (I think). It was
written by Rudy Rucker (a great author, and fun, too) and runs under DOS.
It does NOT have a callable interface, although I believe that you can add
your own rules (via C, PASCAL, etc.). It's pretty neat and comes with a
pretty good manual and lots of examples. It's in color, of course.

P.S. Too bad it doesn't run on the Macintosh. :(

P.P.S. If I totally missed the point of your post and this is of absolutely
no interest or relevance, forgive me.
-- 
------ Dan "Bud" Keith ------------------------------------------------
Odesta Corporation           | busy with subtle thought, distinctions between
mcdchg!ecgcurly!odgate!dbk   | things long held the same, resemblance of things 
                             | long held different. - W.B. Yeats 

From cellular-automata-request@Think.COM  Thu Jul 18 01:20:41 1991
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Date: 11 Jul 91 04:07:54 GMT
From: ojuarez@mtecv2.mty.itesm.mx (Ing. Octavio Juarez Espinoza)
Organization: ITESM. Campus Monterrey
Subject: What's the power of cellular automatas?
Message-Id: <3544@mtecv2.mty.itesm.mx>
Newsgroups: comp.theory.cell-automata
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Hi,

I need to know what the cellular automata are?

The cellular automatas have any future?

Thanks in advance for your information.

Sincerely,


			Octavio Juarez Espinosa
			email ojuarez@mtecv2.mty.itesm.mx
 

From hiebeler@Think.COM  Thu Jul 18 07:08:21 1991
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Date: Thu, 18 Jul 91 07:08:20 EDT
Message-Id: <9107181108.AA13471@custard.think.com>
To: cellular-automata@Think.COM
Subject: Best speed


> What is the best speed (millions of updates a second) that people
> get on CA's?

  I wrote some simple CA code on the Connection Machine a while back.
I was getting something like 132 million cell-updates per second, on a
64K machine.

  I never got around to doing any performance hacking on it, though.
Back when I wrote it, I had some ideas for speeding it up, but I never
went back and worked on that.  I'm sure some serious speed
improvements could be made.

  This speed was measured using lookup-table rules, and basic computed
rules (that are too big for lookup-table).  There isn't too much of a
performance difference between the two, on the CM, unless your
cell-update-function starts getting complicated.

--
Dave Hiebeler                  | Internet: hiebeler@think.com
Thinking Machines Corporation  | UUCP: {uunet,harvard}!think!hiebeler
245 First Street               | Bitnet: hiebeler%think.com@mitvma.bitnet
Cambridge, MA 02142  USA       | Phone:  (617) 234-4070 (work)

From cellular-automata-request@Think.COM  Fri Jul 19 03:20:53 1991
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Date: 11 Jul 91 15:15:35 GMT
From: jb7m+@andrew.cmu.edu (Jon C. R. Bennett)
Organization: Junior, Math/Computer Science, Carnegie Mellon, Pittsburgh, PA
Subject: Xlife 3.0
Message-Id: <ccT7MLC00Vox56PpJ6@andrew.cmu.edu>
Newsgroups: comp.windows.x,comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM

It seems somehow that Xlife 3.0 got removed from export.lcs.mit.edu, I
have put it back, If you have a previous copy, or did not get it the last
time I put it out, you should get a new copy, the new versions main claim
to fame is a new load file format which allows for the inclusion of other
pattern files, specifing offests/rotations, and time offests, allowing
large patterns to be compressed into very small file, and allowing large
patterns to be built with ease, so pick up a copy and enjoy.

jon

p.s. as always if you want to be notified of changes or new patterns send
me mail and I will add you to my mailing list

From cellular-automata-request@Think.COM  Tue Jul 23 15:44:57 1991
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           Tue, 23 Jul 1991 10:48:19 PDT
Date:      Tue, 23 Jul 1991 10:48:15 PDT
From: "David M. Cross" <dcross@west.automatrix.com>
Message-Id: <288c6be4.automwst@west.automatrix.com>
Organization: Automatrix, Inc.  P.O. Box 196  Rexford, NY  12148-0196 USA
Reply-To: "David M. Cross" <dcross@west.automatrix.com>
To: cellular-automata@Think.COM
Subject:   Best speed

David Hiebeler writes:
>> What is the best speed (millions of updates a second) that people
>> get on CA's?
>
>   I wrote some simple CA code on the Connection Machine a while back.
> I was getting something like 132 million cell-updates per second, on a
> 64K machine.

this number is very impressive, and is probably the world record.

with the simplest run-cycle, the peak performance of a single CAM-PC module is
only 24 million cell-updates per second and you would have to run 6 modules in
the same host to achieve the peak performance that you quote.

unfortunately, though the CAM-PC hardware and software is designed for 8
modules, I don't have access to a PC with enough slots to run more than 4 at
once, so I won't be able to break your record anytime soon.  [anyone giving
away an expansion chassis for an IBM PC? :)]

I don't think the folks at MIT have ever run 6 CAM boards together either.
(correct me gently if I'm wrong.)

besides, such a record would be short-lived.  I would guess that with all the
silicon in a 64K CM, you could probably find some clever way to squeeze a
factor of 10 out of the codes.  (oops, I shouldn't have suggested that. :)

david cross

-- 
David M. Cross     EMAIL: dcross@west.automatrix.com         (internet)
                          dcross%west.automatrix.com@cunyvm  (bitnet)
                          uupsi!automwst!dcross              (uupc)

Automatrix, Inc.  --  Cellular Automata Machines (CAM-PC) and CA Software

From cellular-automata-request@Think.COM  Thu Jul 25 14:34:24 1991
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Date: 25 Jul 91 17:09:53 GMT
From: siegelma@yoko.rutgers.edu (hava)
Organization: Rutgers Univ., New Brunswick, N.J.
Subject: Universal Turing Machine
Message-Id: <Jul.25.13.09.52.1991.1409@yoko.rutgers.edu>
Newsgroups: comp.theory,comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM


I'm looking to find the smallest known univeral Turing machine
in term of number of states and size of alphabet...
(I think I'v seen one with 7 letters and 5 states... but i'm not
positive about it....)
Thanks,
  Hava

From cellular-automata-request@Think.COM  Thu Jul 25 15:20:41 1991
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From: leao@buphy.bu.edu (Joao Leao)
Message-Id: <9107251923.AA32599@buphy.bu.edu>
To: siegelma@yoko.rutgers.edu
Cc: ca@Think.COM
In-Reply-To: hava's message of 25 Jul 91 17:09:53 GMT <Jul.25.13.09.52.1991.1409@yoko.rutgers.edu>
Subject: Universal Turing Machine


 The result usually quoted in the literature is from Minsky's
 book (Finite and Infinite Automata) and is (N(states)=7 and
 M(alphabet)=4. Shannon has shown that you can reduce any
 universal T(N,M)-machine to one with N'=2 and M < 4MN+M.
 There are interesting hints on alphabet size minima from
 Chaitin's early work which point toward (M=5,N=5) as the
 most likely minimum. There is not, to my knowledge, a proof of
 minimal (M,N) for universality. I would much like to know
 if there is such a result anywhere. 

 By the way, A.R. Smith (JACM 18,339) has extracted, from 
 Minsky's result a proof that you can have a Universal CA
 with 8 states on an hexagonal neighborhood.



Joao Pedro Leao (Artificial Iconoclast and Director of Computer Resources
Artificial Physics Lab * Boston University - Physics Dept. Boston MA 02215)
 	leao@buphy.bu.edu | leao@buphyc.bitnet | BUPHYC::LEAO 
"Well I am sitting here in Tahiti/ I am laying in the sun and sipping a...
...chartreuse tropical drink!/ and I say: I know those Bermuda shorts!..."


From cellular-automata-request@Think.COM  Thu Jul 25 15:27:59 1991
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To: siegelma@yoko.rutgers.edu (hava)
Cc: ca@Think.COM, minsky@cecelia.media.mit.edu
Subject: Re: Universal Turing Machine 
In-Reply-To: Your message of 25 Jul 91 17:09:53 +0000.
             <Jul.25.13.09.52.1991.1409@yoko.rutgers.edu> 
Date: Thu, 25 Jul 91 15:23:30 EDT
From: Michael Travers <mt@cecelia.media.mit.edu>

    
    I'm looking to find the smallest known univeral Turing machine
    in term of number of states and size of alphabet...
    (I think I'v seen one with 7 letters and 5 states... but i'm not
    positive about it....)

Minsky's 1967 book _Computation:  Finite and Infinite Machines_ presents a
four-symbol, five-state universal TM. 



From cellular-automata-request@Think.COM  Thu Jul 25 15:56:01 1991
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Subject: Re: Universal Turing Machine 
In-Reply-To: Your message of Thu, 25 Jul 91 15:23:30 -0400.
             <9107251923.AA01733@cecelia.media.mit.edu> 
Date: Thu, 25 Jul 91 15:51:47 EDT
From: Michael Travers <mt@cecelia.media.mit.edu>

    From: Michael Travers <mt@cecelia.media.mit.edu>
    
        
        I'm looking to find the smallest known univeral Turing machine
        in term of number of states and size of alphabet...
        (I think I'v seen one with 7 letters and 5 states... but i'm not
        positive about it....)
    
    Minsky's 1967 book _Computation:  Finite and Infinite Machines_ presents a
    four-symbol, five-state universal TM. 
    
Oops, four symbols, seven states is correct as Leao stated.



From cellular-automata-request@Think.COM  Thu Jul 25 17:55:32 1991
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Date: Thu, 25 Jul 91 17:56:52 EDT
From: Marvin Minsky <minsky@media-lab.media.mit.edu>
Message-Id: <9107252156.AA21387@media-lab.media.mit.edu>
To: mt@cecelia.media.mit.edu, minsky@media-lab.media.mit.edu
Cc: siegelma@yoko.rutgers.edu, ca@Think.COM
In-Reply-To: Michael Travers's message of Thu, 25 Jul 91 15:23:30 EDT <9107251923.AA01733@cecelia.media.mit.edu>
Subject: Universal Turing Machine 

It is 4 symbols and 7 states.  Claude Shannon once explained why the
product might be an OK measure of complexity.

It's from around 1963.  So far as I know, it remains the smallest
product.  But the encoding is tricky because it involves a particular
form of Post Tag process.  I have a slightly smaller candidate machine
which might very well be universal -- but there is no proof of the
latter, so it doesn't count yet. 



From cellular-automata-request@Think.COM  Thu Jul 25 18:36:32 1991
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From: leao@buphy.bu.edu (Joao Leao)
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To: minsky@media-lab.media.mit.edu
Cc: mt@cecelia.media.mit.edu, minsky@media-lab.media.mit.edu,
        siegelma@yoko.rutgers.edu, ca@Think.COM
In-Reply-To: Marvin Minsky's message of Thu, 25 Jul 91 17:56:52 EDT <9107252156.AA21387@media-lab.media.mit.edu>
Subject: Universal Turing Machine 


 Thanks for the info, Marvin. Just out of curiosity, what are the
states and symbols for your new candidate?


Joao Pedro Leao (Artificial Iconoclast and Director of Computer Resources
Artificial Physics Lab * Boston University - Physics Dept. Boston MA 02215)
 	leao@buphy.bu.edu | leao@buphyc.bitnet | BUPHYC::LEAO 
"Well I am sitting here in Tahiti/ I am laying in the sun and sipping a...
...chartreuse tropical drink!/ and I say: I know those Bermuda shorts!..."

From cellular-automata-request@Think.COM  Thu Jul 25 18:46:24 1991
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From: Marvin Minsky <minsky@media-lab.media.mit.edu>
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To: leao@buphy.bu.edu, minsky@media-lab.media.mit.edu
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In-Reply-To: Joao Leao's message of Thu, 25 Jul 91 18:39:30 EDT <9107252239.AA01050@buphy.bu.edu>
Subject: Universal Turing Machine 

I don't know because I never kept good notes, confidently believing
that I could always reconstruct anything I ever discovered because of
constantly becoming smarter.  Hmmm.

Anyway, if you look up the discussion in my book "Computation", you'll
find the actual Tag system that obsessed Emil Post: algorithm:
  Begin with a string of 0's and 1's.
  If the string begins with 0, append "00" to the end.
  If the string begins with 1, append "1101" to the end.
  Erase the first THREE digits.
  Repeat!
 
There are various flimsy reasons to suspect that this procedure may be
Turing-Universal and, if so, there would be a primitive-recursive
procedure for encoding any halting problem into the initial string.
No one knows, however, and so far as I know, nothing has been
puiblished about it for two decades.   In any case, I dimly recollect
making a small Turing machine to implement this algorithm but, right
now, I can't see how to get it down to the 13 states required.  

From cellular-automata-request@Think.COM  Thu Jul 25 20:34:27 1991
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Date: 26 Jul 91 00:12:43 GMT
From: eppstein@wormwood.ics.uci.edu (David Eppstein)
Organization: UC Irvine Department of ICS
Subject: Re: Universal Turing Machine
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minsky@media-lab.media.mit.EDU (Marvin Minsky) writes:
> The actual Tag system that obsessed Emil Post: algorithm:
>  Begin with a string of 0's and 1's.
>  If the string begins with 0, append "00" to the end.
>  If the string begins with 1, append "1101" to the end.
>  Erase the first THREE digits.
>  Repeat!
>
> There are various flimsy reasons to suspect that this procedure may be
> Turing-Universal... I can't see how to get it down to the 13 states required.

I can name that Turing machine in 6 states!
You didn't define what happens when the string becomes empty.
In that case my machine goes into a short loop.

Alphabet = { 0, 1, *(= blank) }
Initial state = S0, pointing to start of string

S0: 0 => S1 (0, R)    1 => S2 (1, R)    * => S6 (0, L)
S1: 0 => S1 (0, R)    1 => S1 (1, R)    * => S0 (0, R)
S2: 0 => S2 (0, R)    1 => S2 (1, R)    * => S3 (1, R)
S3: 0 => S4 (*, R)    1 => S4 (*, R)    * => S4 (1, R)
S4: 0 => S5 (*, R)    1 => S5 (*, R)    * => S5 (0, R)
S5: 0 => S0 (*, R)    1 => S0 (*, R)    * => S6 (1, L)
S6: 0 => S6 (0, L)    1 => S6 (1, L)    * => S3 (*, R)
--
David Eppstein    UC Irvine, Info & Computer Science    eppstein@ics.uci.edu

From cellular-automata-request@Think.COM  Thu Jul 25 21:33:54 1991
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Date: 26 Jul 91 00:19:20 GMT
From: eppstein@wormwood.ics.uci.edu (David Eppstein)
Organization: UC Irvine Department of ICS
Subject: Re: Universal Turing Machine
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In article <288F68FB.13204@ics.uci.edu> I write:
> I can name that Turing machine in 6 states!
>
> S0: 0 => S1 (0, R)    1 => S2 (1, R)    * => S6 (0, L)
> ...
> S6: 0 => S6 (0, L)    1 => S6 (1, L)    * => S3 (*, R)

Before anyone else posts this:
Of course, there are seven states here.
Not six.
--
David Eppstein    UC Irvine, Info & Computer Science    eppstein@ics.uci.edu

From cellular-automata-request@Think.COM  Fri Jul 26 08:38:47 1991
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From: siegelma@yoko.rutgers.edu
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To: minsky@media-lab.media.mit.edu, mt@cecelia.media.mit.edu
Subject: Universal Turing Machine
Cc: ca@Think.COM, siegelma@paul.rutgers.edu

Thank you very much for your reply...

I use this result to construct a universal neural network with first order
connections, that I have proved its existence with Eduardo Sontag.
Using the number you have pointed to me about, I managed to build such a 
universal neural network with 555 neurons. The construction is similar to
the counter machine, and hence the number of staters is almost the same. 

The dominant element is the multiplication of states with letters (28) and
the constant (~18)...  I'm sure it is possible to shrink it a little,
but the multiplication and some similar constant seem to me to be necessary.

Do you believe that there is a way to construct a universal counter machine
with much less states?  (Each stack adds one neuron to the result, hence I 
don't mind the number of them.)

     yours,
      Hava

From cellular-automata-request@Think.COM  Fri Jul 26 13:56:45 1991
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Date: Fri, 26 Jul 91 13:56:21 EDT
From: Marvin Minsky <minsky@media-lab.media.mit.edu>
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In-Reply-To: siegelma@yoko.rutgers.edu's message of Fri, 26 Jul 91 08:38:43 EDT <9107261238.AA05981@yoko.rutgers.edu>
Subject: Universal Turing Machine

I have no strong idea about finding the minimum product.  I have
proved that it cannot be less than 8, so the space between 8 and 28 is
open.  (Showing that there are no 2 * 3 Universal machines was quite
tedious.   The product=7 case is trivial -- I think.)


From cellular-automata-request@Think.COM  Mon Jul 29 16:44:55 1991
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Date: Mon, 29 Jul 91 14:44:43 MDT
From: cgl@t13.Lanl.GOV (Chris Langton)
Message-Id: <9107292044.AA27373@t13.lanl.gov>
To: ca@Think.COM
Subject: UTM's and CA's


  As this is the CA discussion list, it might be useful to point
out that Kristian Lindgren and Mats Nordahl have employed Minsky's 
7-state, 4-symbol universal TM in their construction of the  
minimal (currently known) universal 1-dimensional CA.

They have done two embeddings, actually. One requires 7 states in
an r=1 (3-neighbor) rule, and the other requires only 4 states in
an r=2 (5-neighbor) rule. In terms of overall complexity, the
size of the CA rule table (the number of states raised to the 
power of the number of neighbors) is a useful comparative measure. 
On this measure, the 7-state r=1 rule is by far the simplest, 
with a rule table of size 7^3 or 343. This is simpler than LIFE,
with a rule-table of size 512. The 4-state r=2 rule uses a table
of size 4^5 = 1024.

  This simplicity is achieved in part by using a periodic background
rather than a unform background, and in part by using composite 
signals: signals covering more than one cell. If a uniform background 
is used, their embedding requires 9-states for the r=1 CA and 5-states 
for the r=2 CA. 

  Their constructions appear in the paper "Universal Computation
in Simple One-Dimensional Cellular Automata", Complex Systems, 
V4, 1990, pp 299-318.  

------------------------------------------------------------------

Cheers!

   Chris Langton

   Complex Systems Group
   MS B213, Theoretical Division	Phone: (505) 667-9471
   Los Alamos National Laboratory	Email: cgl@t13.lanl.gov
   Los Alamos, New Mexico, USA		FAX:   (505) 665-3003
   87545



From cellular-automata-request@Think.COM  Mon Jul 29 16:59:11 1991
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Date: Mon, 29 Jul 1991 17:02-0400
From: Allan C. Wechsler <ACW@YUKON.SCRC.Symbolics.COM>
Subject: Universal Turing Machine
To: minsky@media-lab.media.mit.edu, siegelma@yoko.rutgers.edu
Cc: mt@cecelia.media.mit.edu, ca@Think.COM
In-Reply-To: <9107261756.AA07854@media-lab.media.mit.edu>
Message-Id: <19910729210215.0.ACW@PALLANDO.SCRC.Symbolics.COM>

    Date: Fri, 26 Jul 1991 13:56 EDT
    From: Marvin Minsky <minsky@media-lab.media.mit.edu>

    I have no strong idea about finding the minimum product.  I have
    proved that it cannot be less than 8, so the space between 8 and 28 is
    open.  (Showing that there are no 2 * 3 Universal machines was quite
    tedious.   The product=7 case is trivial -- I think.)

I'm not sure I see why the product |L||S| is the correct measure, rather
than, say, |L|(|S|)^2 or any other monotonic function of L and S.

What we really have here is a whole collection of extremal problems,
which can be stated "How many states does an l-letter UTM need?" or,
dually, "How many letters does an s-state UTM need?"  The state of the
art is a table illustrating which values of (s,l) have been achieved or
proven impossible.  So far all I've seen is Minsky's (7,4), so the table
looks like this:


S: 2 3 4 5 6 7 8 9 10
L
2  n n ? ? ? ? ? ? ? ...
3  n ? ? ? ? ? ? ? ? ...
4  ? ? ? ? ? y y y y ...
5  ? ? ? ? ? y y y y ...
6  ? ? ? ? ? y y y y ...
7  ? ? ? ? ? y y y y ...
:  : : : : : : : : :

I'm sure there is a 2-letter UTM in the literature: how many states does
it have?  Certainly we could emulate the (7,4) with something like a
(56,2).  Can we do better?

From cellular-automata-request@Think.COM  Mon Jul 29 20:32:12 1991
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Date: Mon, 29 Jul 91 20:31:35 EDT
From: Marvin Minsky <minsky@media-lab.media.mit.edu>
Message-Id: <9107300031.AA04427@media-lab.media.mit.edu>
To: ACW@YUKON.SCRC.Symbolics.COM, minsky@media-lab.media.mit.edu
Cc: siegelma@yoko.rutgers.edu, mt@cecelia.media.mit.edu, ca@Think.COM
In-Reply-To: Allan C. Wechsler's message of Mon, 29 Jul 1991 17:02-0400 <19910729210215.0.ACW@PALLANDO.SCRC.Symbolics.COM>
Subject: Universal Turing Machine

Yes, there are simple, and rather small upper bounds on exchanging
states for symbols and vice versa.  My book "Computation" mentions
them, I think.  

As for the table, consider this one: I wrote a complete simulation
program (with some output formatting deleted), in the
eccentric TECO language (as of MIT, 1974).

 hki1Aul qq+^^0:iqm^[29iiq
 y0L1 00L1 11L2 A1L1
 y0L1 0yR2 1AR2 AyR6
 yyL3 00L0 1AL3 A1L4
 yyL4 0yR5 11L7 A1L4
 yyR5 0yL3 1AR5 A1R5
 yyR6 0AL3 1AR6 A1R6
 y0R7 0yR6 11R7 A0R2
 ^[j<sR^[;-d-2ciql-^^^[ci"ed^^^[cii^[ciuq'^[>
 j<sL^[;-d-2ciql-^^^[ci"ed^^^[cii-2c^[ciuq'^[>
jxblx1lx2lx3lx4lx5lx6lx7hk
 iyyAyyAyy^[32<i0^[>ji110101110000010011011^[ 1uq       <htmbqq=>! 

I do not advise attempting to understand this code, which is almost as
bad as that for the Universal Turing machine.

From cellular-automata-request@Think.COM  Tue Jul 30 00:20:00 1991
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Date: Tue, 30 Jul 91 00:19:39 EDT
From: siegelma@yoko.rutgers.edu
Message-Id: <9107300419.AA06949@yoko.rutgers.edu>
To: ACW@yukon.scrc.symbolics.com, minsky@media-lab.media.mit.edu
Subject: Universal Turing Machine
Cc: ca@Think.COM, mt@cecelia.media.mit.edu, siegelma@yoko.rutgers.edu

Allan raised the question of what is special in the multiplication
|L||S| over any other monotonic function of |L| and |S|...

I can think only of the intuitive answer:
The TM operates by the function f: L*S -> ...
This is the importance of the measure |L||S|. It should be a natural lower
bound for measuring complexity of a TM. (This is also the reason
for |L||S| edges, and for getting this measure while building a TM with
simple computing elements as in Neural Networks, or other restricted models)

Allan asked about a table starting with 2 letters. Is it CLEAR that we can't 
have a TM with 1 letter only?  We can simulate a TM with 3 unary stacks... 
considering 2 unary stacks, I know about the 1960 paper of Minsky 
simulating the TM y=f(x), with 2^y = f(2^x): "Recursive Unsolvability of
Post's Problem of "Tags" ... " Annals of Math. vol 74, 437-455.  
Has anything been found concerning a linear simulation of two unary counters 
since?... 


Hava

From cellular-automata-request@Think.COM  Tue Jul 30 11:27:53 1991
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From: Marvin Minsky <minsky@media-lab.media.mit.edu>
Message-Id: <9107301527.AA03963@media-lab.media.mit.edu>
To: siegelma@yoko.rutgers.edu, minsky@media-lab.media.mit.edu
Cc: ACW@yukon.scrc.symbolics.com, ca@Think.COM, mt@cecelia.media.mit.edu,
        siegelma@yoko.rutgers.edu
In-Reply-To: siegelma@yoko.rutgers.edu's message of Tue, 30 Jul 91 00:19:39 EDT <9107300419.AA06949@yoko.rutgers.edu>
Subject: Universal Turing Machine

Yes, it's clear you can't have a Turing machine with only one symbol,
because then all the squares of the tape have that symbol, and that's
the same as a blank tape.  So you've got a finite-state machine.

I didn't understand your product complexity argument.  The significance
of the state-symbol product is only that it is invariant up to a
constant, because there are simple ways to convert any TM to either a
2 symbol machine or a two-state machine.  However, because of that
(not very big) constant, the product isn't "very invariant" for small
machines...

From cellular-automata-request@Think.COM  Tue Jul 30 13:36:11 1991
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Date: 30 Jul 91 16:15:37 GMT
From: hoey@zogwarg.etl.army.mil (Dan Hoey)
Organization: Naval Research Laboratory, Washington, DC
Subject: Re: Universal Turing Machine
Message-Id: <748@zogwarg.etl.army.mil>
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In article <9107252247.AA22840@media-lab.media.mit.edu> minsky@media-lab.media.mit.EDU (Marvin Minsky) writes:

>Anyway, if you look up the discussion in my book "Computation", you'll
>find the actual Tag system that obsessed Emil Post: algorithm:

>  Begin with a string of 0's and 1's.
>  If the string begins with 0, append "00" to the end.
>  If the string begins with 1, append "1101" to the end.
>  Erase the first THREE digits.
>  Repeat!
 
>There are various flimsy reasons to suspect that this procedure may be
>Turing-Universal....

Are there any inputs on which this Tag system is known to increase
without bound?  Or for which the system even seems to gradually
increase beyond the first few 1000*|Input| steps?

A naive probabilistic analysis indicates that the number of 1's will
stay about the same, and the number of 0's will converge to the number
of 1's.  Is there any particular input for which this behavior seems
not to occur?

Should I go looking for the book to answer these questions, or is
there any better reference on the problem?

Dan Hoey
Hoey@ETL.Army.Mil

From cellular-automata-request@Think.COM  Tue Jul 30 14:12:13 1991
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Date: Tue, 30 Jul 1991 14:15-0400
From: Allan C. Wechsler <ACW@YUKON.SCRC.Symbolics.COM>
Subject: Universal Turing Machine
To: siegelma@yoko.rutgers.edu, ACW@YUKON.SCRC.Symbolics.COM,
        minsky@media-lab.media.mit.edu
Cc: ca@Think.COM, mt@cecelia.media.mit.edu
In-Reply-To: <9107300419.AA06949@yoko.rutgers.edu>
Message-Id: <19910730181537.9.ACW@PALLANDO.SCRC.Symbolics.COM>

    Date: Tue, 30 Jul 1991 00:19 EDT
    From: siegelma@yoko.rutgers.edu

    Allan raised the question of what is special in the multiplication
    |L||S| over any other monotonic function of |L| and |S|...

    I can think only of the intuitive answer:
    The TM operates by the function f: L*S -> ...
    This is the importance of the measure |L||S|. It should be a natural lower
    bound for measuring complexity of a TM. (This is also the reason
    for |L||S| edges, and for getting this measure while building a TM with
    simple computing elements as in Neural Networks, or other restricted models)

    Allan asked about a table starting with 2 letters. Is it CLEAR that we can't 
    have a TM with 1 letter only?  

Perhaps it was /not/ clear that I consider "blank" a letter.  If there
is only one letter, then the TM cannot store information on the tape.
				   
				   We can simulate a TM with 3 unary stacks... 
    considering 2 unary stacks, I know about the 1960 paper of Minsky 
    simulating the TM y=f(x), with 2^y = f(2^x): "Recursive Unsolvability of
    Post's Problem of "Tags" ... " Annals of Math. vol 74, 437-455.  
    Has anything been found concerning a linear simulation of two unary counters 
    since?... 


    Hava

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From: hoey@AIC.NRL.Navy.Mil
Message-Id: <9107310151.AA00402@sun13.aic.nrl.navy.mil>
To: ca@Think.COM
Subject: Re: Universal Turing Machine
In-Reply-To: <748@zogwarg.etl.army.mil>

minsky@media-lab.media.mit.EDU (Marvin Minsky) writes:

>Anyway, if you look up the discussion in my book "Computation", you'll
>find the actual Tag system that obsessed Emil Post: algorithm:

>  Begin with a string of 0's and 1's.
>  If the string begins with 0, append "00" to the end.
>  If the string begins with 1, append "1101" to the end.
>  Erase the first THREE digits.
>  Repeat!
 
>There are various flimsy reasons to suspect that this procedure may be
>Turing-Universal....

I replied:

>A naive probabilistic analysis indicates that the number of 1's will
>stay about the same, and the number of 0's will converge to the number
>of 1's.  Is there any particular input for which this behavior seems
>not to occur?

Well, I ran this on over 1900 random strings of 100 bits, so I have a
better idea of what happens.  In 19% of the cases the string became
empty.  In 81% of the cases, the tag system cycled (the longest cycle
period seen was 58).  In most cases, one or the other case happened in
under 1E5 steps, but a few cases went for over 1E6 steps and one went
for over 6E7 steps before becoming cyclic.

It seems to me that if this system were universal, I would be likely
to stumble across one of the ever-growing strings than this.  I
wouldn't be surprised if this is a terminating tag system, though I
doubt that anyone will be able to prove it.

On the other hand, the 1918th string I tried was

#*00011010011100110000001100010001111100011001010000111101011010-
11101111111100010100111111001110001110

which has gone on for over 1E8 steps, so possibly there is something
to this system.  Still, it hasn't shown any tendency to get steadily
larger--the length has meandered between 20000 and 40000 for most of
the history.  I intend to run this a few billion steps--or until it
terminates, of course.

Does "Computation" discuss computational experience on the problem, or
is there any better reference?

Dan Hoey
Hoey@AIC.NRL.Navy.Mil

From cellular-automata-request@Think.COM  Wed Jul 31 17:35:59 1991
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Date: 26 Jul 91 20:56:02 GMT
From: bbw@lanl.lanl.gov (Burton Wendroff)
Organization: Los Alamos Natl Lab, Los Alamos, N.M.
Subject: Firing Squad Problem
Message-Id: <28617@lanl.lanl.gov>
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R.M. Balzer in his Ph.D. thesis (1966, Carnegie Institute of 
Technology) described an 8-state minimal-time solution of the
one-dimensional firing squad problem. He conjectured that there
is a 7-state minimal-time solution. Does anyone know if this
conjecture has been confirmed or refuted?


From cellular-automata-request@Think.COM  Thu Aug  1 11:04:15 1991
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Date: Thu, 1 Aug 1991 11:08-0400
From: Allan C. Wechsler <ACW@YUKON.SCRC.Symbolics.COM>
Subject: Firing Squad Problem
To: bbw@lanl.lanl.gov, ca@Think.COM
In-Reply-To: <28617@lanl.lanl.gov>
Message-Id: <19910801150813.5.ACW@PALLANDO.SCRC.Symbolics.COM>

    Date: Fri, 26 Jul 1991 16:56 EDT
    From: bbw@lanl.lanl.gov (Burton Wendroff)

    R.M. Balzer in his Ph.D. thesis (1966, Carnegie Institute of 
    Technology) described an 8-state minimal-time solution of the
    one-dimensional firing squad problem. He conjectured that there
    is a 7-state minimal-time solution. Does anyone know if this
    conjecture has been confirmed or refuted?

Does the state count include the "capping state" which is used to mark
the ends of the squad?

Suppose we drop the minimum time restriction.  How many states are
needed to make sure the squad fires in synchrony at all?

I'm also curious about "error recovery" -- that is, how deranged can the
initial state be and still allow the squad to recover and fire in
synchrony -- but I can't form a rigorous query.

From cellular-automata-request@Think.COM  Thu Aug  1 16:32:30 1991
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Date: 1 Aug 91 00:43:32 GMT
From: jgk@osc.COM (Joe Keane)
Organization: Versant Object Technology, Menlo Park, CA
Subject: Re: Universal Turing Machine
Message-Id: <4957@osc.COM>
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Using the number of states as a measure is interesting from a theoretical
point of view.  It assumes we have a combinatorial `black box', for example a
ROM, to generate the next state.  It also assumes that the only thing that
matters is the size of this table.

Let me suggest an alternative.  We know that when you're implementing
combinatorial functions, you tend to use PLAs rather than ROMs.  The reason is
that in real applications, the desired functions aren't random and can be
better implemented with a little analysis rather than a brute-force lookup
table.

So then, i think an interesting way to measure the complexity of a CA is by
counting the number of gates per cell needed to implement it.  We can assume
that we have latches for the state variables driven by some external clock.
So for simplicity, we can concentrate only on the combinatorial part.  First
we have to come up with some binary encoding for the states, which i can only
offer some heuristics for.  Once that's done, it's a simple matter of gate
minimization, which is a well-known problem.

I think it's also interesting to consider asynchronous design, so that the CA
is unclocked and has no latches at all.  Certainly i can take an arbitrary CA
and add the appropriate handshaking to make it asynchronous.  But i doubt this
will make an efficient design in terms of the number of gates.  I think what
you'll find is that it's better to start with a CA which has many states but
simple rules than one which is optimized for the number of states.

One thing that may not be obvious is that it's often better to use more bits
to encode the state than are strictly necessary.  A redundant encoding can
greatly simply the logic needed to compute the next state.  You may consider
some signals to be state and others to be intermediate results, but the gates
don't care about this.

Playing with asynchronous automata is sort of a hobby of mine, and i've done a
number of interesting circuits, for example bit queues.  But i've never tried
universal machines, so i'm curious to know if anyone has done this.
--
Joe Keane, amateur mathematician
jgk@osc.com (...!uunet!stratus!osc!jgk)

From cellular-automata-request@Think.COM  Thu Aug  1 17:32:19 1991
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Date: 1 Aug 91 19:58:47 GMT
From: mayne@aleph.cs.fsu.edu (William Mayne)
Organization: Florida State University Dept. of Computer Science
Subject: Asynchronous CA?
Message-Id: <1991Aug1.195847.13958@mailer.cc.fsu.edu>
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I am just a lurker in comp.theory.cell-automata, but some principles
of CA may be useful to me in other work. Please indulge me for the
following possibly silly question.

The discussions of CA which I have seen here and elsewhere always
seem to assume synchronous execution. I can see the usefulness of
this assumption. But is it absolutely necessary? Has anyone looked
seriously at the consequences of relaxing the requirement for
synchronous execution in CA? My intuition is that although it
would make many things harder it wouldn't necessarily degenerate
into useless chaos.

To illustrate what I mean here are some possible schemes:

(1) In each time step only a subset of cells execute a transition.
The determination of which cells execute could be random, possibly
constrained by fairness, i.e. every cell must execute infinitely
often (in any infinite sequence). A more reasonable but semi-synchronous
rule would be that each cell must execute with a given frequency
distribution.

(2) Separate the reading of neighbor states from the change of a cell's
own state - modeling computation time for the transition, i.e. at time=t
read a neighbor's state. At some later time t+d change state to a function
of the neighbors' states. During the interval continue to report the state
at t. The interval d could be random.

(3) Permit the reading of states of different neighbors to happen
at different times. The interval between the reads and between the
last read and change of local state could be random.

Bill Mayne

From cellular-automata-request@Think.COM  Thu Aug  1 22:21:25 1991
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Date: 1 Aug 91 22:02:28 GMT
From: mroussel@alchemy.chem.utoronto.ca (Marc Roussel)
Organization: Department of Chemistry, University of Toronto
Subject: Re: Asynchronous CA?
Message-Id: <1991Aug1.220228.5417@alchemy.chem.utoronto.ca>
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In article <1991Aug1.195847.13958@mailer.cc.fsu.edu> mayne@cs.fsu.edu writes:
>The discussions of CA which I have seen here and elsewhere always
>seem to assume synchronous execution.
>Has anyone looked
>seriously at the consequences of relaxing the requirement for
>synchronous execution in CA?
>To illustrate what I mean here are some possible schemes:
>
>(1) In each time step only a subset of cells execute a transition.
>The determination of which cells execute could be random, possibly
>constrained by fairness, i.e. every cell must execute infinitely
>often (in any infinite sequence). A more reasonable but semi-synchronous
>rule would be that each cell must execute with a given frequency
>distribution.
>
>(2) Separate the reading of neighbor states from the change of a cell's
>own state - modeling computation time for the transition, i.e. at time=t
>read a neighbor's state. At some later time t+d change state to a function
>of the neighbors' states. During the interval continue to report the state
>at t. The interval d could be random.
>
>(3) Permit the reading of states of different neighbors to happen
>at different times. The interval between the reads and between the
>last read and change of local state could be random.

     Both (1) and (2) have been done.  In particular, a lot of genetic
algorithm programs do something like (2).  I don't know about (3).
Interestingly, random update rules such as Bill suggests often
(always?) lead to behaviour that is qualitatively quite similar to that
obtained in simultaneous update schemes.  (In other words, random
updates don't usually produce any interesting new behaviour.)  If anyone
knows of a counter example, I'm sure we'd all like to know about it.
Also, if anyone knows why random updates don't normally affect the
qualitative behaviour of CA's, I'd love to hear it.

                                Sincerely,

				Marc R. Roussel
                                mroussel@alchemy.chem.utoronto.ca

P.S.: In case any mathematicians are listening in, by similar
qualitative behaviour I of course mean essentially identical statistical
properties of whatever property is being simulated averaged over a large
number of initial configurations.

From cellular-automata-request@Think.COM  Fri Aug  2 16:15:25 1991
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From: autodesk!air!rudy@fernwood.mpk.ca.us (Rudy Rucker)
Message-Id: <9108021957.AA08500@air.acad>
To: ca@Think.COM
Subject: asynchronous CAs


One asynchronous CA which has been investigated a lot is the
cyclic competition rule of Griffeath and Fish.  Here at each update,
each cell looks at only one of its eight neighbors, using a randomizer
to decide which neighbor.  The cells range over some fixed 
number of states 0,1,2,...N-1.  If the cell's neighbor has a state
one higher than the cell (with 0 and N thought of as the same state)
the cell is "eaten" by the neighbor and takes on the new state.

The value of looking at only one neighbor is that the "rule" or "lookup
table" for the CA becomes simpler, smaller, and faster.  

Cyclic competition, by the way, reliably produces Belusov-Zhabotinsky
spirals.  Griffeath has an interesting disk that shows some of his
rules, a smaller sampling of them is also available as part of 
Autodesk's "James Gleick's Chaos The Software" package.

I used the "look at one random neighbor" trick to implement a three
species Wator world, in which three kinds of cells eat, age, and
reproduce.  In this kind of simulation, you need a lot of bits per
cell to maintain info about he cell's age, etc.  I used 8 bits per
cell.  If one wanted to update a cell on the basis of all eight of
its neighbors, this would be too many bits to deal with.  So instead
I used a randomizer and looked only at one neighbor each time and then
had a total of only 16 bits to deal with.  An extra trick I used
here was to then swap the resulting valuesof the pair of cells to
create a brownian drift...though this is not wihtout pitfalls given
that the screen is updated tope to bottom.

From cellular-automata-request@Think.COM  Fri Aug  2 19:44:05 1991
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Date: 2 Aug 91 22:03:02 GMT
From: mayne@aleph.cs.fsu.edu (William Mayne)
Organization: Florida State University Dept. of Computer Science
Subject: Re: asynchronous CAs
Message-Id: <1991Aug2.180302.12557@mailer.cc.fsu.edu>
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In article <9108021957.AA08500@air.acad> rudy@air.UUCP (Rudy Rucker) writes:
>
>One asynchronous CA which has been investigated a lot is the
>cyclic competition rule of Griffeath and Fish.  Here at each update,
>each cell looks at only one of its eight neighbors, using a randomizer
>to decide which neighbor...

This is interesting, but since it is the second reply to concentrate
on randomness rather than aynchronousness (asynchronicity?) I am
begining to think I blew my explanation. The point of the randomness
I mentioned didn't have to do with the transitions being random,
but with the timing of the transitions being undetermined. Randomly
selecting cells to execute in each time step of a simulation was
intended just to capture that timing aspect, not that the transitions
were random except in that they depended upon neighbor's states read
at undetermined times. The new-state function could be a deterministic
function of the values actually read. (Actually doesn't "function",
strictly speaking, imply determinism. If one element of the input (range)
could lead to more than one output or new state (range) what we have is
a relation, not a function. Right? Or is usage in automata theory looser?)
Does that seem like a reasonable way to define an asynchronous CA
abstractly?

This is actually an important problem for me since my actual work
involves asynchronous parallel execution where computing elements,
though not uniform like CA, communicate with a fixed and relatively
small set of neighbors. My assumption has been that a discrete time
model with undefined atomic updating sequences would capture this.

Actual random-element CAs also sound interesting, though.

Bill Mayne

From cellular-automata-request@Think.COM  Sat Aug  3 04:38:59 1991
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Date: 2 Aug 91 15:49:28 GMT
From: karakots@apple.com (Ken Karakotsios)
Organization: Apple Computer
Subject: Re: Asynchronous CA?
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References:<1991Aug1.195847.13958@mailer.cc.fsu.edu> <1991Aug1.220228.5417@alchemy.chem.utoronto.ca>

In article <1991Aug1.220228.5417@alchemy.chem.utoronto.ca> 
mroussel@alchemy.chem.utoronto.ca (Marc Roussel) writes:
> Also, if anyone knows why random updates don't normally affect the
> qualitative behaviour of CA's, I'd love to hear it.
> 
>                                 Sincerely,
> 
>                                 Marc R. Roussel
>                                 mroussel@alchemy.chem.utoronto.ca
> 

My guess is that, since CAs are (typically) serial simulations of a 
parallel process, there is some flexability in how you can update the 
cells without affecting the dynamics of the system.  If you have a 
present-state array and a next-state array for your CA simulation, then it 
certainly doesn't matter what order you stuff new values into your 
next-state array, because you are not changing your present-state array, 
which is the only source of state for computing your next-state.   

If you update your next-state array a random number of times before 
replacing the present state array, then some of your cells in the next-state array may not get 
updated each generation.  This may cause some local deviations from the 
dynamics of deterministic updating, but if the number of cells not getting 
updated is low in comparison to the total number of cells, then the 
overall dynamics should still prevail.   

This seems to make sense, because lots of CA rules will retain the same 
dynamics, independent of the starting pattern (sometimes with the 
exception of very special starting pattern).  I.e., most random starting 
patterns for "life" seem to produce a similar mix of the standard gliders, 
oscillators, and other stuff.   Its only a few special starting patterns, 
like a glider gun, that produce dynamics that are much different from the 
average behavior.   

Probably, the most "interesting" CA rules (on the edge 
of chaos) will have the greatest sensitvity to the updating scheme, 
because they will have the highest probability of generating differing 
dynamics with different starting patterns.

Best regards,

Ken Karakotsios
karakots@apple.com

From cellular-automata-request@Think.COM  Sat Aug  3 16:38:49 1991
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Date: 3 Aug 91 20:27:25 GMT
From: aboulang@bbn.com (Albert Boulanger)
Organization: BBN, Cambridge MA
Subject: Re: asynchronous CAs
Message-Id: <ABOULANG.91Aug3162719@taurus.bbn.com>
Newsgroups: comp.theory.cell-automata
References: <9108021957.AA08500@air.acad>
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In article <1991Aug2.180302.12557@mailer.cc.fsu.edu> mayne@aleph.cs.fsu.edu
(William Mayne) writes:

   This is interesting, but since it is the second reply to concentrate
   on randomness rather than aynchronousness (asynchronicity?) I am
   begining to think I blew my explanation. The point of the randomness
   I mentioned didn't have to do with the transitions being random,
   but with the timing of the transitions being undetermined. Randomly
   selecting cells to execute in each time step of a simulation was
   intended just to capture that timing aspect, not that the transitions
   were random except in that they depended upon neighbor's states read
   at undetermined times.

One can consider the asynchronous transactions between computing
elements to be a random selection of a family of delay difference
equations with a discrete delay parameter. (This is similar to IFS
systems.) A Lyapunov Stability treatment like this appeared in:

"On the Stability of Asynchronous Iterative Processes"
John Tistsiklis, Math. Systems Theory, 20, 137-153, 1987

Another model that has been used is to have a notion of two times:

  1) Neighborhood Sampling rate (faster than #2)

  2) Internal state update rate 

This model seems to have been developed by both Ising (spin-glass
simulation) and neural network people:

"Efficient Parallel Simulations of Asynchronous Cellular Arrays"
Boris Lubachevsky, Complex Systems 1, 1099-1123, 1987.

"Efficient Distributed Event-Driven Simulations of Multiple-Loop Networks",
Boris Lubachevsky, Comm of the ACM, Vol 32 No 1, 111-131, Jan 1989

"Stochastic Dynamics of Neural Networks",
Pierre Peretto and Jean_Jaques Niez, IEEE Trans, Systems, Man, and Cybernetics,
Vol SMC-16, No 1, 73-83, Jan/Feb 1986.

When looking at the spin-glass literature one must be careful at what
the spin-glass people term "asynchronous". They mean serial updating
because of the problem of detailed balance. (This is a condition that
assures the system will reach the Boltzmann distribution at
equilibrium.) This issue and the criteria for convergence discussed in
the book "Parallel and Numerical Computation: Numerical Methods",
referenced below is discussed in:

"`Chaotic Relaxation` in Concurrently Asynchronous Neural Dynamics"
Jacob Barhen and Sandeep Guiati, IJCNN 1989 Proceedings (June 18-22)
I-619,I-626.

Breaking the detailed balance condition, yet maintaining the Boltzmann
distribution in cellular automata is discussed in:

"Stochastic Cellular Automata with Gibbsian Invariant Measures", Jose
Marroquin and Arturo Ramirez, IEEE Trans Info. Theory, Vol 37, No 3,
541-551, May 1991.

Here are two other refs that I have that discuss asynchronous cellular automata:

"Structure in Asynchronous Cellular Automata"
T.E. Ingerson and R.L. Buvel
Physica 10D, 59-68, 1984

"Integration of Phase-Difference Relations in Asynchronous Sequential Networks"
Tommaso Toffoli in
Automata Languages and Programming, eds unknown, Springer Verlag,
457-463, 1978

   This is actually an important problem for me since my actual work
   involves asynchronous parallel execution where computing elements,
   though not uniform like CA, communicate with a fixed and relatively
   small set of neighbors. My assumption has been that a discrete time
   model with undefined atomic updating sequences would capture this.


A good book on asynchronous numerical methods is:

"Parallel and Numerical Computation: Numerical Methods",
Demetri Bertsekas, & John Tsitsiklis, Prentice-Hall 1989


By my collective asynchronous being,

Albert Boulanger
aboulanger@bbn.com

From cellular-automata-request@Think.COM  Mon Aug  5 12:39:50 1991
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Date: 5 Aug 91 09:52:48 GMT
From: egnr76@castle.ed.ac.uk (A Kashko)
Organization: Edinburgh University
Subject: Re: Asynchronous CA?
Message-Id: <12042@castle.ed.ac.uk>
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In article <15197@goofy.Apple.COM> karakots@apple.com (Ken Karakotsios) writes:
>References:<1991Aug1.195847.13958@mailer.cc.fsu.edu> <1991Aug1.220228.5417@alchemy.chem.utoronto.ca>
>
>In article <1991Aug1.220228.5417@alchemy.chem.utoronto.ca> 
>mroussel@alchemy.chem.utoronto.ca (Marc Roussel) writes:
>> Also, if anyone knows why random updates don't normally affect the
>> qualitative behaviour of CA's, I'd love to hear it.
>> 
>>                                 Sincerely,
>> 
>>                                 Marc R. Roussel
>>                                 mroussel@alchemy.chem.utoronto.ca
>> 
>
>My guess is that, since CAs are (typically) serial simulations of a 
>parallel process, there is some flexability in how you can update the 
>cells without affecting the dynamics of the system.  If you have a 
>present-state array and a next-state array for your CA simulation, then it 
>certainly doesn't matter what order you stuff new values into your 
>next-state array, because you are not changing your present-state array, 
>which is the only source of state for computing your next-state.   
	Hmm, I've written some CA's on SIMD parallel machines, and 
it seems to me that CA's are just special cases of Markov Random Fields.
The trick, on a parallel machine is to update each processing element
with its neighbours held fixed. This is why one uses chequerboard updating
or (on the AMT DAP) crinkled mappings. As the size of the neighbourhood gets
larger, (or for three dimensional arrays) any error in computing the  Markov
potential gets relatively smaller (the surface-volume ratio decreases).
With this type of updating you change your present state array in a number
of incremental steps. It occurs to me that random updating, provided the 
probability a site is selected for updating is not too large, will result
in selecting a number of Markov Isolated sites, and the qualiatative dynamics
will not be changed, although the time to equilibrium may well change.
>
>If you update your next-state array a random number of times before 
>replacing the present state array, then some of your cells in the next-state array may not get 
>updated each generation.  This may cause some local deviations from the 
	UNfortunately some may get update twice, possibly resulting in
incorrect updating.
>dynamics of deterministic updating, but if the number of cells not getting 

	This seems to make sense only if you miss out the "not", I am afraid.

>updated is low in comparison to the total number of cells, then the 
>overall dynamics should still prevail.   
>
>This seems to make sense, because lots of CA rules will retain the same 
>dynamics, independent of the starting pattern (sometimes with the 
	Well, any automaton, if left to run on its own, will fall into 
a cyclical pattern, and if you treat CA from a thermodynamic viewpoint
one would expect the cyclic patterns achieved to be in the densest part
of phase space. The dynamics should be unchanged (with probability one).

>Probably, the most "interesting" CA rules (on the edge 
>of chaos) will have the greatest sensitvity to the updating scheme, 
>because they will have the highest probability of generating differing 
>dynamics with different starting patterns.
	BUt see my remarks on nieghbourhood size above. These CA will have a small
neighbourhood size, and effects will take a long time to propogate through the system.
>

From cellular-automata-request@Think.COM  Wed Aug  7 09:21:33 1991
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Date: Wed, 7 Aug 1991 09:25-0400
From: Allan C. Wechsler <ACW@YUKON.SCRC.Symbolics.COM>
Subject: Attention Stu Card!
To: CA@Think.COM
Message-Id: <19910807132552.6.ACW@PALLANDO.SCRC.Symbolics.COM>

I apologize for bothering the whole CA list, but I'm trying to debug a
network difficulty.

Attention, Stu Card!  I've been trying to get through to you as
Stu@sct60a.sunyct.edu, and I've been getting No-such-host errors.  How
can I get through to you?  Respond to me only, of course.

From cellular-automata-request@Think.COM  Sun Aug 11 07:39:56 1991
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Date: 11 Aug 91 10:58:19 GMT
From: kido@math.keio.ac.jp (Takashi Kido)
Organization: Faculty of Sci. and Tech., Keio Univ., Yokohama, Japan.
Subject: Wolfram's experiment
Message-Id: <KIDO.91Aug11195819@sapphire.math.keio.ac.jp>
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 I am interested in the Wolfram's work.

He said in the book ,"Theory and application of Cellular Automata" , as following.
 "Cellular automata are discrete dynamical systems with simple construction
 but complex self-organizing behavior. Evidence is presented that all one-dimensional cellular automata fall into four 
distinct universality classes. Characterizations of the structures generated in these classes are discussed.Three classes 
exhibit behaviour analogous to limit points,limit cycles and chaotic attractors.The forth class is probably capable of 
universal computation,so that properties of its infinite time behaviour are undecidable."

 I want to experiment and analyze it,Does any one have any good tools,which can simulate various types of Cellular automata,and 
analyze,such as density or entropies or etc.

How can we apply this results on the computer science? 
For example,can we apply it for Neural-Network?
If anyone had good comment,or reference,would you please tell me about that.






                                                                                  Thank you very much.

                                            
                                                                          


                                                                                -----------------------------------
                                                                                 kido@nak.math.keio.ac.jp
                                                                                        KIDO TAKASHI
                                                                                ----------------------------------- 


--

                       **************************************
                       $@!v(J  $@7D1~Bg3XM}9)3XItCf@>8&5f<<(J       $@!v(J  
                       $@!v(J                                   $@!v(J 
                       $@!v(J           $@>k8M(J  $@N4(J (takashi kido) $@!v(J  
                       ************************************** 
                        

From cellular-automata-request@Think.COM  Tue Aug 13 13:40:23 1991
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Date: 13 Aug 91 16:29:44 GMT
From: rdb@turing.scs.carleton.ca (Robert D. Black)
Organization: School of Computer Science, Carleton University, Ottawa, Canada
Subject: Restricted Halting Problem?
Message-Id: <1991Aug13.162944.2355@cunews.carleton.ca>
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Is it possible to apply the undecidability of the Halting problem
to a *particular* turing machine M, with arbitrary input?

In other words, does there exist a sufficiently complex turing machine
M for which the question of whether M halts on arbitrary input is
undecidable?  If such a machine exists, would it have to be capable
of universal computation?

Thanks for the help!

--
--
Robert Black                               rdb@scs.carleton.ca
School of Computer Science
Carleton University, Ottawa, Canada

From cellular-automata-request@Think.COM  Tue Aug 13 13:58:30 1991
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Date: Tue, 13 Aug 1991 14:01-0400
From: Allan C. Wechsler <ACW@YUKON.SCRC.Symbolics.COM>
Subject: Restricted Halting Problem?
To: rdb@turing.scs.carleton.ca, ca@Think.COM
In-Reply-To: <1991Aug13.162944.2355@cunews.carleton.ca>
Message-Id: <19910813180103.1.ACW@PALLANDO.SCRC.Symbolics.COM>

    Date: Tue, 13 Aug 1991 12:29 EDT
    From: rdb@turing.scs.carleton.ca (Robert D. Black)

    Is it possible to apply the undecidability of the Halting problem
    to a *particular* turing machine M, with arbitrary input?

    In other words, does there exist a sufficiently complex turing machine
    M for which the question of whether M halts on arbitrary input is
    undecidable?
Certainly, since universal turing machines exist -- for example, the
4-letter, 7-state machine discussed recently in this forum.
		  If such a machine exists, would it have to be capable
    of universal computation?
That's a more interesting question.  The obvious examples are universal,
and universal certainly implies undecidable.  But I'm clueless about the
other direction.  My intuition is that there are probably undecidable
TMs that are not universal.

    Thanks for the help!

    --
    --
    Robert Black                               rdb@scs.carleton.ca
    School of Computer Science
    Carleton University, Ottawa, Canada

From cellular-automata-request@Think.COM  Wed Aug 14 15:40:57 1991
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Date: Wed, 14 Aug 91 18:46:50 GMT
From: ies@riesz.mit.edu (Irving E. Segal)
Organization: Department of Mathematics, Wellesley College
Subject: Re: Restricted Halting Problem?
Message-Id: <1991Aug14.184650.22542@galois.mit.edu>
Newsgroups: comp.theory.cell-automata,sci.logic
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In article <19910813180103.1.ACW@PALLANDO.SCRC.Symbolics.COM> ACW@YUKON.SCRC.Symbolics.COM (Allan C. Wechsler) writes:
>
>    Date: Tue, 13 Aug 1991 12:29 EDT
>    From: rdb@turing.scs.carleton.ca (Robert D. Black)
>
>    Is it possible to apply the undecidability of the Halting problem
>    to a *particular* turing machine M, with arbitrary input?
>
>    In other words, does there exist a sufficiently complex turing machine
>    M for which the question of whether M halts on arbitrary input is
>    undecidable?
>Certainly, since universal turing machines exist -- for example, the
>4-letter, 7-state machine discussed recently in this forum.
>		  If such a machine exists, would it have to be capable
>    of universal computation?

I'm fairly sure the answer is NO.  It's been a while since I've studied
logic, but I believe the question you are asking is equivalent to:
are all recursively enumerable but not recursive sets Turing reducible to
one another, and the answer is no, there are lots of "degrees" of 
unsolvability between recursive and below "universal r.e.".  
I think any logician worth his or her salt can help you out here... 
I believe Spector, for example,
has made a detailed study of this question, showing, for example, that
Turing reducibility is not a linear ordering in this region of the
hierarchy (above "recursive" and below "universal r.e.").



From cellular-automata-request@Think.COM  Wed Aug 14 17:42:42 1991
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Date: 14 Aug 91 19:38:29 GMT
From: eifrig@server.cs.jhu.edu (Jack Eifrig)
Subject: Restricted Halting Problem?
Message-Id: <eifrig.682199534@emanon.cs.jhu.edu>
Newsgroups: comp.theory.cell-automata,sci.logic
Sender: ca-request@Think.COM
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In article <1991Aug14.184650.22542@galois.mit.edu> ies@riesz.mit.edu (Irving E. Segal) writes:
>In article <19910813180103.1.ACW@PALLANDO.SCRC.Symbolics.COM> ACW@YUKON.SCRC.Symbolics.COM (Allan C. Wechsler) writes:
>>
>>    Date: Tue, 13 Aug 1991 12:29 EDT
>>    From: rdb@turing.scs.carleton.ca (Robert D. Black)
>>
>>    Is it possible to apply the undecidability of the Halting problem
>>    to a *particular* turing machine M, with arbitrary input?
>>
>>    In other words, does there exist a sufficiently complex turing machine
>>    M for which the question of whether M halts on arbitrary input is
>>    undecidable?
>>Certainly, since universal turing machines exist -- for example, the
>>4-letter, 7-state machine discussed recently in this forum.
>>		  If such a machine exists, would it have to be capable
>>    of universal computation?
>
>I'm fairly sure the answer is NO.  It's been a while since I've studied
>logic, but I believe the question you are asking is equivalent to:
>are all recursively enumerable but not recursive sets Turing reducible to
>one another, and the answer is no, there are lots of "degrees" of 
>unsolvability between recursive and below "universal r.e.".

	Well, this is a simple question, but depending on what you mean by
"halting on arbitrary input," the answer is vacuously "yes" or vacuously "no."
If you're talking about "Does there exist a TM whose halting problem with
respect to an arbitrary input is undecidable," then of course the answer is
"yes."  The existence of universal TM's is well-understood, as Allan points
out.  This is of course the same problem as the general Halting Problem, since
the universal TM just "Godelizes" the problem.
	On the other had, if you mean "Does there exist a TM whose halting
problem with respect to _all_ inputs is undecidable," then of course the answer
is "no."  Every TM either halts with respect to every input or it does not;
in either case, one of the stupid decision procedures "All TM's halt" or "All
TM's do not halt" decides the problem correctly.

-------------------------------------------------------------------------------

	"Young man, in mathematics you don't understand things, you
just get used to them."

					- John von Neumann

-------------------------------------------------------------------------------

From cellular-automata-request@Think.COM  Wed Aug 14 18:05:31 1991
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Date: Wed, 14 Aug 1991 18:08-0400
From: Allan C. Wechsler <ACW@YUKON.SCRC.Symbolics.COM>
Subject: Restricted Halting Problem?
To: eifrig@server.cs.jhu.edu, ca@Think.COM
In-Reply-To: <eifrig.682199534@emanon.cs.jhu.edu>
Message-Id: <19910814220807.8.ACW@PALLANDO.SCRC.Symbolics.COM>

    Date: Wed, 14 Aug 1991 15:38 EDT
    From: eifrig@server.cs.jhu.edu (Jack Eifrig)


    In article <1991Aug14.184650.22542@galois.mit.edu> ies@riesz.mit.edu (Irving E. Segal) writes:
    >In article <19910813180103.1.ACW@PALLANDO.SCRC.Symbolics.COM> ACW@YUKON.SCRC.Symbolics.COM (Allan C. Wechsler) writes:
    >>
    >>    Date: Tue, 13 Aug 1991 12:29 EDT
    >>    From: rdb@turing.scs.carleton.ca (Robert D. Black)
    >>
    >>    Is it possible to apply the undecidability of the Halting problem
    >>    to a *particular* turing machine M, with arbitrary input?
    >>
    >>    In other words, does there exist a sufficiently complex turing machine
    >>    M for which the question of whether M halts on arbitrary input is
    >>    undecidable?
    >>Certainly, since universal turing machines exist -- for example, the
    >>4-letter, 7-state machine discussed recently in this forum.
    >>		  If such a machine exists, would it have to be capable
    >>    of universal computation?
    >
    >I'm fairly sure the answer is NO.  It's been a while since I've studied
    >logic, but I believe the question you are asking is equivalent to:
    >are all recursively enumerable but not recursive sets Turing reducible to
    >one another, and the answer is no, there are lots of "degrees" of 
    >unsolvability between recursive and below "universal r.e.".

	    Well, this is a simple question, but depending on what you mean by
    "halting on arbitrary input," the answer is vacuously "yes" or vacuously "no."
    If you're talking about "Does there exist a TM whose halting problem with
    respect to an arbitrary input is undecidable," then of course the answer is
    "yes."  The existence of universal TM's is well-understood, as Allan points
    out.  This is of course the same problem as the general Halting Problem, since
    the universal TM just "Godelizes" the problem.
	    On the other had, if you mean "Does there exist a TM whose halting
    problem with respect to _all_ inputs is undecidable," then of course the answer
    is "no."  Every TM either halts with respect to every input or it does not;
    in either case, one of the stupid decision procedures "All TM's halt" or "All
    TM's do not halt" decides the problem correctly.

I don't think he meant either of your proposed paraphrases.  I think he
meant, "Does there exist a TM whose halting problem with respect to
arbitrary input is undecidable, but which is NOT universal?"  We know
universality implies halting-problem-undecidability; what about the
converse?

    -------------------------------------------------------------------------------

	    "Young man, in mathematics you don't understand things, you
    just get used to them."

					    - John von Neumann

    -------------------------------------------------------------------------------

Gosh, that's deep.  I think it generalizes from "mathematics" to
"Life, the Universe, and Everything".

From cellular-automata-request@Think.COM  Thu Aug 15 02:40:38 1991
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Date: 14 Aug 91 16:21:15 GMT
From: gtephx!baligag@bloom-beacon.MIT.EDU (Ganesh Baliga)
Organization: AGCS
Subject: re: Restricted Halting Problem ?
Message-Id: <1991Aug14.162115.10610@gtephx.UUCP>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM

>Is it possible to apply the undecidability of the Halting problem
>to a *particular* turing machine M, with arbitrary input?
>
>In other words, does there exist a sufficiently complex turing machine
>M for which the question of whether M halts on arbitrary input is
>undecidable?  If such a machine exists, would it have to be capable
>of universal computation?

A machine which has the halting set as its domain serves your
first purpose. 

Your second question has a negative answer. There are r.e, non 
recursive sets having "complexity strictly less" than the 
complexity of the halting set (This was Emil Post's problem and
it was solved by Friedberg and Muchnik).

Choose your favorite set satisfying the above property and
a machine having this set as its domain, and what you have
is a complex machine which is not capable of universal
computation. And of course, it's domain is undecidable.

>
>Thanks for the help!

Hope that helps!

>
>--
>--
>Robert Black                               rdb@scs.carleton.ca
>School of Computer Science
>Carleton University, Ottawa, Canada

Cheers,

Ganesh

From cellular-automata-request@Think.COM  Fri Aug 16 07:40:47 1991
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Date: 1 Aug 91 22:02:28 GMT
From: mroussel@alchemy.chem.utoronto.ca (Marc Roussel)
Organization: Department of Chemistry, University of Toronto
Subject: Re: Asynchronous CA?
Message-Id: <1991Aug1.220228.5417@alchemy.chem.utoronto.ca>
Newsgroups: comp.theory.cell-automata
References: <1991Aug1.195847.13958@mailer.cc.fsu.edu>
Sender: ca-request@Think.COM
To: ca@Think.COM

In article <1991Aug1.195847.13958@mailer.cc.fsu.edu> mayne@cs.fsu.edu writes:
>The discussions of CA which I have seen here and elsewhere always
>seem to assume synchronous execution.
>Has anyone looked
>seriously at the consequences of relaxing the requirement for
>synchronous execution in CA?
>To illustrate what I mean here are some possible schemes:
>
>(1) In each time step only a subset of cells execute a transition.
>The determination of which cells execute could be random, possibly
>constrained by fairness, i.e. every cell must execute infinitely
>often (in any infinite sequence). A more reasonable but semi-synchronous
>rule would be that each cell must execute with a given frequency
>distribution.
>
>(2) Separate the reading of neighbor states from the change of a cell's
>own state - modeling computation time for the transition, i.e. at time=t
>read a neighbor's state. At some later time t+d change state to a function
>of the neighbors' states. During the interval continue to report the state
>at t. The interval d could be random.
>
>(3) Permit the reading of states of different neighbors to happen
>at different times. The interval between the reads and between the
>last read and change of local state could be random.

     Both (1) and (2) have been done.  In particular, a lot of genetic
algorithm programs do something like (2).  I don't know about (3).
Interestingly, random update rules such as Bill suggests often
(always?) lead to behaviour that is qualitatively quite similar to that
obtained in simultaneous update schemes.  (In other words, random
updates don't usually produce any interesting new behaviour.)  If anyone
knows of a counter example, I'm sure we'd all like to know about it.
Also, if anyone knows why random updates don't normally affect the
qualitative behaviour of CA's, I'd love to hear it.

                                Sincerely,

				Marc R. Roussel
                                mroussel@alchemy.chem.utoronto.ca

P.S.: In case any mathematicians are listening in, by similar
qualitative behaviour I of course mean essentially identical statistical
properties of whatever property is being simulated averaged over a large
number of initial configurations.

From cellular-automata-request@Think.COM  Wed Aug 21 11:55:58 1991
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Date: 21 AUG 91 09:30:46 CST
From: wsimpson@uwpg02.uwinnipeg.ca
Organization: MIT PLASMA FUSION CENTER
Subject: CA tools for MacP
Message-Id: <21AUG91.09304607@uwpg02.uwinnipeg.ca>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM

Can anyone recommend a cellular automata package for the Mac?
Thanks very much for any help.

-Bill Simpson
wsimpson@uwpg02.uwinnipeg.ca

From cellular-automata-request@Think.COM  Wed Aug 21 19:56:31 1991
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Date: Wed, 21 Aug 91 16:23:09 PDT
From: autodesk!air!rudy@fernwood.mpk.ca.us (Rudy Rucker)
Message-Id: <9108212323.AA03958@air.acad>
To: ca@Think.COM
Subject: CA tools for Mac


There is a good Mac CA package called CA-Sim, and written by
Ken Karakatsios.  He sells them himself with doc for, I believe,
under $50.  To get more info, email him at
karakots@apple.com

From cellular-automata-request@Think.COM  Thu Aug 22 11:55:56 1991
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Date: 22 Aug 91 14:56:46 GMT
From: diamond@hubcap.clemson.edu (David Lee)
Organization: Clemson University
Subject: ARCHIVES-Where?
Message-Id: <1991Aug22.145646.7682@hubcap.clemson.edu>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
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Could someone e-mail me the archive site for the postings in this group?


Thanks,
    David Lee
    diamond@hubcap.clemson.edu


-- 
   David C Lee                           Friends, Amiga's aren't perfect, but 
   Clemson University     //             the alternatives suck the chrome off
   Clemson,SC           \X/ Amiga	 a trailer hitch at 20 yards.
   diamond@hubcap.clemson.edu	

From hiebeler@Think.COM  Thu Aug 22 17:24:41 1991
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From: David Hiebeler <hiebeler@Think.COM>
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Date: Thu, 22 Aug 91 17:25:01 EDT
Message-Id: <9108222125.AA03267@passion.think.com>
To: diamond@hubcap.clemson.edu
Cc: ca@Think.COM
In-Reply-To: David Lee's message of 22 Aug 91 14:56:46 GMT <1991Aug22.145646.7682@hubcap.clemson.edu>
Subject: ARCHIVES-Where?


  You can get archives for the CA mailing-list/newsgroup (which are
coupled to each other, for those who weren't aware) via anonymous FTP
to think.com (131.239.2.1).  They are in the subdirectory "mail".  The
following archives are available (the first 4 are compressed):

  ca.archive-1987.Z
  ca.archive-1988.Z
  ca.archive-1989.Z
  ca.archive-1990.Z
  ca.archive-1991

I think the archive mechanism wasn't working for much of 1990, it
looks like things between May-December 1990 didn't get saved.

--
Dave Hiebeler                  | Internet: hiebeler@think.com
Thinking Machines Corporation  | UUCP: {uunet,harvard}!think!hiebeler
245 First Street               | Bitnet: hiebeler%think.com@mitvma.bitnet
Cambridge, MA 02142  USA       | Phone:  (617) 234-4070 (work)

From cellular-automata-request@Think.COM  Fri Aug 23 13:56:44 1991
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Date: 23 Aug 91 17:31:53 GMT
From: coleman@sundae10.DAB.GE.COM (Richard Coleman)
Organization: GE Aerospace, SCSD
Subject: Re: Call for discussion - comp.ai.ga or comp.ai.genetic-algorithms
Message-Id: <1991Aug23.173153.13775@ge-dab.GE.COM>
Newsgroups: sci.math.num-analysis,news.groups,sci.math,comp.ai,comp.theory.cell-automata
References: <12521@castle.ed.ac.uk>
Sender: ca-request@Think.COM
To: ca@Think.COM

|> Request For Discussion: Creation of comp.ai.ga or comp.ai.genetic-algorithms.
|>  
|> I have had several requests to post this request. I am cross-posting to
|> news.groups.announce, comp.ai, comp.ai.neural-nets.
|>  
|> PURPOSE:
|>     I (We) are proposing the formation of a newsgroup to discuss topics
|> concerning or related to genetic algorithms. Other topic areas might be
|> machine-based learning systems, such as classifiers, goal-seekers, 
|> game-players, reward/punishment and parallel implementations since these 
|> often employ genetic techniques.
|> 	Hybrid systems and combinations of other techniques (neural networks,
|> N(logN) systems) could be discussed, as well as domain-specific
|> (heuristic) techniques versus genetic techniques.
|>     Announcements about international/national/local conferences and/or
|> college courses might be posted. Proceedings, papers, books, articles
|> can be announced.
|>  

I think this is a good idea, but since genetic algorithms are not limited
to applications in ai, I would think something like comp.genetic-alg
would be a better name.  Also, how would this group be related to
comp.ai.neural-nets and comp.theory.cell-automata.  Alot of the ideas 
are very similar.  Maybe it would be better to increase interaction between
these groups rather than decrease it.  I would personally like to see something
like sci.complex-sys  where people could talk about the study of complex systems
in general (a la Santa Fe Institute).
-- 
Richard Coleman                               The price of freedom
GE Aerospace                                  is eternal vigilance
Simulation & Control Systems Dept.
coleman@sunny.dab.ge.com

From cellular-automata-request@Think.COM  Fri Aug 23 17:56:00 1991
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Date: 23 Aug 91 20:51:14 GMT
From: coleman@sundae10.DAB.GE.COM (Richard Coleman)
Organization: GE Aerospace, SCSD
Subject: books by Santa Fe Institute
Message-Id: <1991Aug23.205114.21335@ge-dab.GE.COM>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM

How could I get a list of conference proceedings and other
books that have been published by the Santa Fe Institute for the 
Study of Complex Systems (I think that's the name).  I looking
for any books on the study of complex systems in general.
-- 
Richard Coleman                               The price of freedom
GE Aerospace                                  is eternal vigilance
Simulation & Control Systems Dept.
coleman@sunny.dab.ge.com

From cellular-automata-request@Think.COM  Fri Aug 23 17:56:15 1991
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Date: 23 Aug 91 21:00:42 GMT
From: johng@OCE.ORST.EDU (John A. Gregor)
Organization: College of Oceanography - Oregon State University
Subject: Re: Call for discussion - comp.ai.ga or comp.ai.genetic-algorithms
Message-Id: <1991Aug23.210042.4179@usenet@CS.ORST.EDU>
Newsgroups: sci.math.num-analysis,news.groups,sci.math,comp.ai,comp.theory.cell-automata
References: <12521@castle.ed.ac.uk>, <1991Aug23.173153.13775@ge-dab.GE.COM>
Sender: ca-request@Think.COM
To: ca@Think.COM

In article <1991Aug23.173153.13775@ge-dab.GE.COM> coleman@sunny.dab.ge.com (Richard Coleman) writes:
||> Request For Discussion: Creation of comp.ai.ga or comp.ai.genetic-algorithms.
||> PURPOSE:
||>     I (We) are proposing the formation of a newsgroup to discuss topics
||> concerning or related to genetic algorithms. Other topic areas might be
||> machine-based learning systems, such as classifiers, goal-seekers, 
||> game-players, reward/punishment and parallel implementations since these 
||> often employ genetic techniques.
|
|I think this is a good idea, but since genetic algorithms are not limited
|to applications in ai, I would think something like comp.genetic-alg
|would be a better name.  

Sorry for the two-liner, but doesn't comp.theory.self-org-sys fit the bill
already?  Perhaps we could change it's name...

JohnG
-- 
John A. Gregor
College of Oceanography			 E-mail: johng@oce.orst.edu
Oregon State University			Voice #: +1 503 737-3022
Oceanography Admin Bldg. #104		  Fax #: +1 503 737-2064
Corvallis, OR  97331-5503

From cellular-automata-request@Think.COM  Tue Aug 27 02:56:56 1991
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Date: 27 Aug 91 05:55:08 GMT
From: rpandey@mist.CS.ORST.EDU (Rajeev Pandey)
Organization: Computer Science Department, Oregon State Univ.
Subject: Re: suggestions for intro finite automata text
Message-Id: <1991Aug27.055508.24952@usenet@CS.ORST.EDU>
Newsgroups: comp.edu,comp.theory,comp.theory.cell-automata
References: <2163@manta.NOSC.MIL>
Sender: ca-request@Think.COM
To: ca@Think.COM


plantz@manta.NOSC.MIL (Glen W. Plantz) writes:

> Any suggestions for a gook Introductory book on Finite Automata? I'm going

 Some standard books that I have handy are as follows:

   Minsky's "Computation: Finite and Infinite Machines"
      (a classic, but I'm not sure about it being introductory)

   Cohen's "Introduction to Computer Theory"
      (a wordy book, but definitely introductory)

   Linz's "An Introduction to Formal Languages and Automata"
      (concise, covers a lot of ground)

   Sudkamp's "Languages and Machines"
      (has a section that is a pretty good tie-in to compilers)

   Lewis and Papadimitriou's "Elements of the Theory of Computation"
      (good references after each chapter)

 I should point out that most of these are considered undergraduate texts,
 the classic graduate text is:

   Hopcroft and Ullman's "Introduction to Automata Theory, Languages and
   Computation"

 Hope this is of some help.



-- 

Department of Computer Science    | Rajeev Pandey 
Dearborn Hall 303                 |    Internet: rpandey@cs.orst.edu 
Oregon State University           |    UUCP: hp-pcd!orstcs!rpandey

From cellular-automata-request@Think.COM  Tue Aug 27 12:56:51 1991
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Date: 27 Aug 91 16:01:32 GMT
From: skip@taygeta.oc.nps.navy.mil (Skip Carter)
Subject: Re: books by Santa Fe Institute
Message-Id: <2676@taurus.cs.nps.navy.mil>
Newsgroups: comp.theory.cell-automata
References: <1991Aug23.205114.21335@ge-dab.GE.COM>
Sender: ca-request@Think.COM
To: ca@Think.COM


 	The Santa Fe Institute books are published by Addison-Wesley.   My copy of the
proceedings on Lattice Gas Methods (published in 1990) lists the following books:

	Proceedings Volumes

	I.	Emerging Synthesis in Science, 1987	David Pines, ed
	II.	Theoretical Immunology, Part I 1988	Alan S. Perelson, ed
	III.	Theoretical Immunology, Part II 1988	""
	IV.	 Lattice Gas Methods of Partial 		Gary D. Doolen et. al.  ed
		 Differential Equations
	V.	 The Economy as an Evolving Complex System  Philip W. Anderson et. al. ed
	VI.	 Artificial Life: Proceedings of an Interdisciplinary     Christopher G. Langton ed
		 Workshop on the Synthesis and Simulation of
		Living Systems
	VII.	Computers and DNA			 George I. Bell & Tom Marr eds

	Lectures Volumes

	I.	Lectures in the Sciences of  Complexity	Daniel L. Stein



-- 
   Everett (Skip) Carter		Phone:  408-646-3318 FAX: 408-646-2712
   Naval Postgraduate School	        INTERNET: skip@taygeta.oc.nps.navy.mil
   Dept. of Oceanography, Code OC/CR    UUCP:     ...!uunet!taygeta!skip
   Monterey, CA. 93934                  TELEMAIL: s.carter/omnet

From cellular-automata-request@Think.COM  Tue Aug 27 14:17:54 1991
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Date: Tue, 27 Aug 91 14:17:34 EDT
From: leao@buphy.bu.edu (Joao Leao)
Message-Id: <9108271817.AA07939@buphy.bu.edu>
To: skip@taygeta.oc.nps.navy.mil
Cc: ca@Think.COM
In-Reply-To: Skip Carter's message of 27 Aug 91 16:01:32 GMT <2676@taurus.cs.nps.navy.mil>
Subject: books by Santa Fe Institute


 Skip,
 Your lis is missing at least one recent volume:

       VII. 	Complexity, Entropy and the Physics of Information
		(ed.) Wojciech H. Zurek
		Proc. of 1989 Workshop...

 I know only because I bought the paperback copy.
 Thanks for posting the other ones though.

						Joao Leao

Joao Pedro Leao (Artificial Iconoclast and Director of Computer Resources
Artificial Physics Lab * Boston University - Physics Dept. Boston MA 02215)
 	leao@buphy.bu.edu | leao@buphyc.bitnet | BUPHYC::LEAO 
"Well I am sitting here in Tahiti/ I am laying in the sun and sipping a...
...chartreuse tropical drink!/ and I say: I know those Bermuda shorts!..."

From cellular-automata-request@Think.COM  Wed Aug 28 03:57:09 1991
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Date: 28 Aug 91 06:22:19 GMT
From: vangogh@ucscb.ucsc.edu (vangogh)
Organization: University of California, Santa Cruz; Open Access Computing
Subject: Genetic algorithms
Message-Id: <20084@darkstar.ucsc.edu>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM


I saw an article in the San Jose Mercury News this morning about a "computer
creature" which piqued my interest.  Would anyone know whether the program
described below is accessible via usenet?  Has he published a paper?

A "creature" consisting only of ones and zeros has emerged from its computer
womb and caused a scientific sensation:  Without human guidance it reproduces,
undergoes spontaneous genetic changes, passes them on to offspring, and 
evolves new species whose interactions mimic those of real biological evolution
and ecology.

The creature, actually an 80-line computer program, is the work of 
Dr. Thomas S. Ray, a plant biologist at the University of Delaware, wo became
a computer expert to study the underlying dynamics of life.

The descendants of what Ray calls his "ancestor creature" can now evolve on 
their own, and some have devised clever ways (completely unforeseen by Ray) 
to multiply, gain advantage over competitors, and stave off extinction.

His "creature" has some very unusual features.  Not only can the sequence and
type of its instructions undergo spontaneous change, but the program creates
its own central processing unit, in effect, a computer.

etc.

From cellular-automata-request@Think.COM  Wed Aug 28 04:56:43 1991
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Date: 28 Aug 91 07:35:03 GMT
From: dbakin@netcom.COM (David Bakin)
Organization: Bakin's Bits
Subject: Lucas' C implementation of Gosper's hash-Life
Message-Id: <1991Aug28.073503.10283@netcom.COM>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM


In the 1990 archives someone mentions "Lucas' C implementation of
Gosper's hash-Life".  I couldn't find it on think.com.  Can someone
mail me a copy or point me to an archive machine?  THANKS!  (I've already
got the article.)  -- Dave

-- 
dbakin@netcom.com      David S. Bakin      (415) 567-4485
"Actually, I'm not the Tooth Fairy.  I'm the Plaque Fairy -- and I'm here
 to remind you to floss."

From cellular-automata-request@Think.COM  Wed Aug 28 05:56:45 1991
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Date: Tuesday, 27 Aug 1991 14:08:05 WUT
From: <NN1@awiwuw11.wu-wien.ac.at>
Organization: Wirtschaftsuniversitaet Wien, Vienna, Austria
Subject: Re: suggestions for intro finite automata text
Message-Id: <91239.140805NN1@awiwuw11.wu-wien.ac.at>
Newsgroups: comp.edu,comp.theory,comp.theory.cell-automata
References: <2163@manta.NOSC.MIL>
Sender: ca-request@Think.COM
To: ca@Think.COM

I will do two advices:

 (i) YOU should look for an "automata and formal languages" textbook since
     finite automata are usually taught together with other computation
     device models (like push-down automata, Turing machines etc.)
(ii) ALL OF US should think whether this comp.theory group has to be
     moderated in order to avoid silly questions like seeking for famous
     textbooks ....

Petr Lisonek, RISC-Linz, Austria.

From cellular-automata-request@Think.COM  Wed Aug 28 10:19:25 1991
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Date: Wed, 28 Aug 1991 10:21-0400
From: Allan C. Wechsler <ACW@YUKON.SCRC.Symbolics.COM>
Subject: Genetic algorithms
To: vangogh@ucscb.ucsc.edu, ca@Think.COM
In-Reply-To: <20084@darkstar.ucsc.edu>
Message-Id: <19910828142111.2.ACW@PALLANDO.SCRC.Symbolics.COM>

I believe Dr. Ray is a CA subscriber.  Regardless, you can reach him:

Ray@Brahms.UDel.Edu
or
Thomas S. Ray
School of Life and Health Sciences
University of Delaware
Newark, Delaware 19716


From cellular-automata-request@Think.COM  Wed Aug 28 11:57:09 1991
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Date: 28 Aug 91 13:50:51 GMT
From: fishwick@fish.cis.ufl.edu (Paul Fishwick)
Organization: U of Florida. Computer Science Dept.
Subject: Re: suggestions for intro finite automata text
Message-Id: <30763@uflorida.cis.ufl.EDU>
Newsgroups: comp.edu,comp.theory,comp.theory.cell-automata
References: <2163@manta.NOSC.MIL>, <1991Aug27.055508.24952@usenet@CS.ORST.EDU>
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If your interest is in the relationship between automata theory
and dynamical systems I would recomend:



System Theory: A Unified State-Space Approach to Continuous
               and Discrete Time Systems

by Padulo and Arbib, 1974, Hemisphere Publishing Corp., Washington, DC

-paul f.

From cellular-automata-request@Think.COM  Wed Aug 28 11:57:12 1991
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Date: Wed, 28 Aug 91 15:03:25 GMT
From: biesel@thrall.sim.es.com (Heiner Biesel)
Organization: Evans & Sutherland Computer Corp., Salt Lake City, UT
Subject: Re: suggestions for intro finite automata text
Message-Id: <1991Aug28.150325.22492@javelin.sim.es.com>
Newsgroups: comp.edu,comp.theory,comp.theory.cell-automata
References: <2163@manta.NOSC.MIL>, <91239.140805NN1@awiwuw11.wu-wien.ac.at>
Sender: ca-request@Think.COM
To: ca@Think.COM

In article <91239.140805NN1@awiwuw11.wu-wien.ac.at> 
<NN1@awiwuw11.wu-wien.ac.at> writes:
>I will do two advices:
>
> (i) YOU should look for an "automata and formal languages" textbook since
>     finite automata are usually taught together with other computation
>     device models (like push-down automata, Turing machines etc.)
>(ii) ALL OF US should think whether this comp.theory group has to be
>     moderated in order to avoid silly questions like seeking for famous
>     textbooks ....
>
>Petr Lisonek, RISC-Linz, Austria.

On the contrary, asking for information, references, help etc. is exactly
what this kind of group should be about. Whether the questions are elementary
or not, and whether the information requested could be easily obtained by
other means is not a criterion for appropriateness. The notion that this
group, which has very little traffic to begin with, should be moderated
to keep people from asking "silly" questions is offensive to me, and I
suspect to others as well. Requests for recommendations for introductory 
and/or advanced textbooks from novices in the field are IMHO welcome.

Regards,
       Heiner biesel@thrall.sim.es.com

From cellular-automata-request@Think.COM  Wed Aug 28 15:57:23 1991
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Date: Wed, 28 Aug 91 19:10:59 GMT
From: yxt3@po.CWRU.Edu (Yoshiyasu Takefuji)
Organization: Case Western Reserve University, Cleveland, Ohio, (USA)
Subject: neural network tutorial
Message-Id: <1991Aug28.191059.4231@usenet.ins.cwru.edu>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM




A tutorial entitled "Successful Neural Network Parallel Computing," will be give
n by
Professor Yoshiyasu Takefuji (Case Western Reserve University) in the Internatio
nal Joint
Conference on Neural Networks of '91 Singapore on November 18, 1991.

Topics covered in the tutorial include
neuron models (sigmoid neuron, McCulloch-Pitts neuron, hysteresis McCulloch-Pitt
s
neuron, maximum neuron),
molecular biology problems (predicting the secondary structure of RNA molecules)
,
games (N-queen problems, knight's tour problems, tiling problems, Hip games),
A tutorial entitled "Successful Neural Network Parallel Computing," will be
given by Professor Yoshiyasu Takefuji (Case Western Reserve University)
in the International Joint Conference on Neural Networks of
'91 Singapore on November 18, 1991.

Topics covered in the tutorial include
neuron models (sigmoid neuron, McCulloch-Pitts neuron,
hysteresis McCulloch-Pitts neuron, maximum neuron),
molecular biology problems (predicting the secondary structure of
RNA molecules),
games (N-queen problems, knight's tour problems, tiling problems, Hip games),
communication problems (crossbar switch scheduling),
sorting/string searching,
graph coloring (four-coloring and k-colorability),
other graph problems (maximum independent set problems,
max cut, maximum clique),
balanced incomplete block design problems,
reliability problems (spare allocation problems),
VLSI CAD problems (graph planarization, channel routing, module orientation prob
lems),
maximum neural networks.

The reprints of the covered topics are also included in the tutorial hand-out.

For the further information about the tutorial and the conference, contact to
Professor Robert Marks II (email: marks@blake.acs.washington.edu)
or
Professor Toshio Fukuda (email: d43131a@nucc.cc.nagoya-u.ac.jp)
or
Professor Russell Eberhart (email: rce1@aplvm.bitnet)
or
Professor Tech-Seng Low (email: elelowts@nusvm.bitnet)


From cellular-automata-request@Think.COM  Wed Aug 28 15:57:42 1991
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Date: 28 Aug 91 19:35:44 GMT
From: rthomson@mesa.dsd.es.com (Rich Thomson)
Organization: Design Systems Division, Evans & Sutherland, SLC, UT
Subject: Journal of Complex Systems, Volume 5, Number 3
Message-Id: <1991Aug28.193544.11030@dsd.es.com>
Newsgroups: comp.theory.cell-automata,comp.theory.dynamic-sys,comp.theory.self-org-sys,alt.fractals
Sender: ca-request@Think.COM
To: ca@Think.COM

June 1991
Volume 5, Number 3

Genetic Algorithms and the Variance of Fitness..................265
    David E. Goldberg and Mike Rudnick

Evolution of Bit Strings: Some Preliminary Results..............279
    Harald Freund and Robert Wolter

Large-Step Markov Chains for the Traveling Salesman Problem.....299
    Olivier Martin, Stgeve W. Otto, and Edward W. Felten

A Two-Dimensional Genetic Algotihm for the Ising Problem........327
    Charles A. Anderson, Kathryn F. Jones and Jennifer Ryan

Structure and Uncomputability in One-Dimensional Maps...........335
    Eric J. Friedman

Fixed Points of Majority Rule Cellular Automata with Application to
Plasticity and Precision of the Immune System...................351
    Zvia Agur

-- 
  ``Read my MIPS -- no new VAXes!!'' -- George Bush after sniffing freon
	    Disclaimer: I speak for myself, except as noted.
UUCP: ...!uunet!dsd.es.com!rthomson			Rich Thomson
Internet: rthomson@dsd.es.com	IRC: _Rich_		PEXt Programmer

From cellular-automata-request@Think.COM  Thu Aug 29 05:56:56 1991
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Date: 29 Aug 91 08:58:48 GMT
From: steve@canon.co.uk (Steve Marsh)
Organization: Canon Research Europe, Guildford, UK
Subject: Re: books by Santa Fe Institute
Message-Id: <1991Aug29.085848.21554@canon.co.uk>
Newsgroups: comp.theory.cell-automata
References: <2676@taurus.cs.nps.navy.mil>, <9108271817.AA07939@buphy.bu.edu>
Sender: ca-request@Think.COM
To: ca@Think.COM

There's another one that I know of-

Artificial Life II, Proceedings Volume, volume X in the SFI series

Steve

-- 
  Steve Marsh. steve@canon.co.uk to 31st August, spm@cs.stir.ac.uk afterwards.
:-x   A Virtual Kiss. (How *can* you get a computer to understand good and bad?)
From cellular-automata-request@Think.COM  Thu Aug 29 05:56:54 1991
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Date: 29 Aug 91 08:59:59 GMT
From: steve@canon.co.uk (Steve Marsh)
Organization: Canon Research Europe, Guildford, UK
Subject: Re: books by Santa Fe Institute
Message-Id: <1991Aug29.085959.21614@canon.co.uk>
Newsgroups: comp.theory.cell-automata
References: <2676@taurus.cs.nps.navy.mil>, <9108271817.AA07939@buphy.bu.edu>
Sender: ca-request@Think.COM
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Ooops, forgot the details...

Artificial Life II

Editors:   Christopher G. Langton, Charles E. Taylor, J. Doyne Farmer,
	   and Steen Rasmussen.



Sorry bout that...
Steve

-- 
  Steve Marsh. steve@canon.co.uk to 31st August, spm@cs.stir.ac.uk afterwards.
:-x   A Virtual Kiss. (How *can* you get a computer to understand good and bad?)

From cellular-automata-request@Think.COM  Thu Aug 29 05:56:59 1991
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Date: 29 Aug 91 05:37:49 GMT
From: minar@reed.edu (Nelson Minar)
Organization: Reed College, Portland, OR
Subject: Tierra (was Re: Genetic algorithms)
Message-Id: <m0kFf4a-0000XFC@vishnu.reed.edu>
Newsgroups: comp.theory.cell-automata
References: <20084@darkstar.ucsc.edu>
Sender: ca-request@Think.COM
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In article <20084@darkstar.ucsc.edu> vangogh@ucscb.ucsc.edu (vangogh) writes:
>I saw an article in the San Jose Mercury News this morning about a "computer
>creature" which piqued my interest.  Would anyone know whether the program
>described below is accessible via usenet?  Has he published a paper?

The program mentioned in the paper is called "Tierra", and it is
written by Thomas Ray, ray@brahms.udel.edu. In fact, he even mentioned
that the program itself might become available.  Is this true? Anyone
have it?

He posted about it on Usenet a few months ago. The article describing
Tierra has/will be published as:

Ray, T. S.  In Press.  An approach to the synthesis of life.
In: Artificial Life II, Santa Fe Institute Studies in the Sciences of
Complexity, vol. XI, (Farmer, J. D., C. Langton, S. Rasmussen, & C. Taylor,
eds).  Redwood City, CA: Addison-Wesley, 1991.

Anyway, I'm sure the author can describe Tierra better than I can, but
it seems to me to be a Core Wars whose programs mutate. This is not as
trivial as it might seem as you have to develop an object code that
takes mutations well. Mr. Ray has done exactly that.

The original 80 line program is something that just contains code to
copy itself. Virus programs evolve, ones which don't contain the
complete code to copy itself but instead borrow other's code, and then
anti-virus programs, etc.
--
		__ 
minar@reed.edu  \/                                        Love under will.

From cellular-automata-request@Think.COM  Thu Aug 29 06:57:13 1991
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Date: 29 Aug 91 09:42:56 GMT
From: jhaataja@finsun.csc.fi (Juha Haataja)
Organization: Centre for Scientific Computing, Finland
Subject: Proceedings of the Workshop on Cellular Automata available
Message-Id: <jhaataja.683458976@finsun>
Newsgroups: comp.theory.cell-automata,comp.theory.dynamic-sys
Sender: ca-request@Think.COM
To: ca@Think.COM


A Workshop on Cellular Automata was arranged at Centre for Scientific
Computing on April 17-18, 1991. The proceedings of the workshop are
now available at nominal cost.

Below you find information about the proceedings (contents and
ordering information) in LaTeX format.

- Juha Haataja, CSC

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

\documentstyle{article}

\begin{document}

\title{Workshop on \\ Cellular Automata \\ Proceedings}
\author{Centre for Scientific Computing \\ Espoo, Finland}
\date{August 29, 1991}
\maketitle

\section{Ordering information}

Below you will find information for ordering the proceedings of the
Workshop on Cellular Automata organized by the Centre for Scientific
Computing on April 17--18, 1991.

We have available a small amount of copies of the proceedings. Because
of billing expenses, ordering a single copy is expensive (the cost of
billing is more than the cost of printing a single copy)---so, you
may want to make your order together with others. Also, if there
aren't too many requests, we may be able to send you a free copy. A
copy has already been sent to all the speakers at the workshop.

If you want to order more than one copy, the cost is 45 FIM (the
printing costs) for each copy of the proceedings (approx.\ 10 USD).
Shipping and billing add 50 FIM (approx.\ 12 USD) to the price of your
order.  Thus, to get just one copy costs 95 FIM---this is why you may
want to consider making your order together with other people.
 
The mail address for ordering is
 
\begin{tabular}{l}
  Ms.\ Paula M\"aki-V\"alkkil\"a \\
  VTKK/TLP \\
  P.O. Box 40 (Street address: Tietotie 6) \\
  SF-02101 Espoo \\
  Finland \\
\end{tabular}

For questions you can use e-mail address {\tt maki@csc.fi}, and
telefax +358 0 457 2302.  If you want to use phone, contact Mr.\ Juha
Haataja; the phone number is +358 0 457 2731.

We hope you enjoy reading the articles included in the proceedings.

\section{Contents of the proceedings}

The papers included in the proceedings have been organized in three parts: 
(a) a tutorial of CA by Jarkko Kari, (b) the four invited speakers, 
and (c) contributed papers.

\begin{enumerate}
\item Jarkko Kari, University of Turku, Finland \\
{\em Basic Properties of Cellular Automata}
\item Per Bak, Brookhaven National Laboratory, USA \\ 
{\em Self-organized Critical Cellular Automata} \\
(An abstract and a list of references are printed.)  
\item Bruce M. Boghosian, Thinking Machines Corporation, USA \\ 
{\em A Survey of Lattice Gas and Lattice Boltzmann Methods for Hydrodynamics}
\item David Griffeath, University of Wisconsin, USA \\
{\em Excitable Cellular Automata}
\item Clifford A. Pickover, IBM T.J. Watson  Research Center, USA \\ 
{\em Visualization of Complex Phenomena}
\item Daniel Azzi, University of Illinois \\ 
{\em Modeling of Diffusion}    
\item Erkki Kurenniemi, Heureka, Finland \\
{\em Cellular automaton model of space and matter}
\item Francis T. Marchese and Jean F. Coppola, Pace University, USA\\
{\em Simulating Ionic Crystal Growth Through Cellular Automata}
\item Bruno Martin, Ecole Normale Sup\'erieure de Lyon, France \\
{\em Intrinsic Universal Computation of One Dimensional Cellular Automata}
\item Jacqueline Signorini, Universite Paris, France \\
{\em Programming Tools for Very Large Scale Cellular Computers}
\item Manne Stenberg and H{\aa}kan Nygren, University of G\"oteborg, Sweden \\
{\em Cellular Automata Simulations of Aggregation in Adsorbed Protein Layers}
\item Veronique Terrier, Ecole Normale Sup\'erieure de Lyon, France  \\ 
{\em Signals in Linear Cellular Automata}
\end{enumerate}

\end{document}
 
 
 

From cellular-automata-request@Think.COM  Thu Aug 29 21:37:57 1991
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	id AA18511; Thu, 29 Aug 91 21:38:36 EDT
Date: Thu, 29 Aug 91 21:38:36 EDT
From: leao@buphy.bu.edu (Joao Leao)
Message-Id: <9108300138.AA18511@buphy.bu.edu>
To: ca@Think.COM
Cc: leao@buphy.bu.edu
Subject: Chris Langton's talk at BU.


 For the benefit of those in the Boston Area, here is an announcement of
 talk you don't want to miss: (Hope you don't mind, Chris!)

Place:  Boston University - Physics Dept
Date:	Friday, September 6 
Time:	12 noon 
Room:	SCI 352

                         
                 Phase Transitions and Computation 

                         Chris Langton
                         
                     Complex Systems Group
                     Theoretical Division
                  Los Alamos National Laboratory

			 Abstract:

In studies of Cellular Automata (CA) it has been found that the most
complex dynamics, including the capacity for universal computation, 
is found in the vicinity of a phase transition in the space of CA
rules. This phase transition exhibits many of the properties of 
a second order --- or "critical" --- transition, suggesting a
relationship between universal computation and critical dynamics.

---------------------------------------------------------------------------

Joao Pedro Leao (Artificial Iconoclast and Director of Computer Resources
Artificial Physics Lab * Boston University - Physics Dept. Boston MA 02215)
 	leao@buphy.bu.edu | leao@buphyc.bitnet | BUPHYC::LEAO 
"Well I am sitting here in Tahiti/ I am laying in the sun and sipping a...
...chartreuse tropical drink!/ and I say: I know those Bermuda shorts!..."




From cellular-automata-request@Think.COM  Fri Aug 30 02:57:22 1991
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Date: 29 Aug 91 18:12:38 GMT
From: dbk@odgate.odesta.com (Dan Keith)
Organization: Emergent Systems
Subject: Re: Journal of Complex Systems, Volume 5, Number 3
Message-Id: <1991Aug29.181238.1970@odgate.odesta.com>
Newsgroups: comp.theory.cell-automata
References: <1991Aug28.193544.11030@dsd.es.com>
Sender: ca-request@Think.COM
To: ca@Think.COM

rthomson@mesa.dsd.es.com (Rich Thomson) writes:

>June 1991
>Volume 5, Number 3

>Genetic Algorithms and the Variance of Fitness..................265
>    David E. Goldberg and Mike Rudnick

[ more table of contents stuff omitted ]

>-- 
>  ``Read my MIPS -- no new VAXes!!'' -- George Bush after sniffing freon
>	    Disclaimer: I speak for myself, except as noted.
>UUCP: ...!uunet!dsd.es.com!rthomson			Rich Thomson
>Internet: rthomson@dsd.es.com	IRC: _Rich_		PEXt Programmer

Why are you posting this table of contents? Is the actual journal available
electronically? If so, I would like to read it; you've piqued my interest.
Or am I missing the point of your posting?
-- 
-- Dan "Bud" Keith does not share these opinions with his employer. --
Odesta Corporation         | Our choice: Free America or Drug-free Amerika.
mcdchg!ecgcurly!odgate!dbk |

From cellular-automata-request@Think.COM  Fri Aug 30 15:57:46 1991
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Date: 30 Aug 91 19:29:42 GMT
From: rthomson@mesa.dsd.es.com (Rich Thomson)
Organization: Design Systems Division, Evans & Sutherland, SLC, UT
Subject: Journal of Complex Systems, Volume 5, Number 2 (+address)
Message-Id: <1991Aug30.192942.16403@dsd.es.com>
Newsgroups: comp.theory.cell-automata,comp.theory.dynamic-sys,comp.theory.self-org-sys,alt.fractals
Sender: ca-request@Think.COM
To: ca@Think.COM


    ``Complex Systems

     A journal devoted to the rapid publication of research on the
     science, mathematics, and engineering of systems with simple
     components but complex overall behaviour.

     Editor:	Stephen Wolfram,
		Wolfram Research, Inc., and University of Illinois''


    Volume 5, Number 2

    Phase-Space Study of Bistable Cellular Automata.............127
	Philippe Bindir, Carol Twining, and David Sherrington

    Real-Coded Genetic Algorithms, Virtual Alphabets, and
    Blocking...................................................139
	David E. Goldberg

    Geometry and Airthmetic of a Simple Cellular Automaton.....169
	Burton Voorhees

    Equivalence Class Analysis of Genetic Algorithms...........183
	Nocholas J. Radcliffe

    Demystifying Quantum Mechanics: A Simple Universe with
    Quantum Uncertainty........................................207
	Gar L. Drescher
    
    Comparison of Inductive versus Deductive Learning
    Networks...................................................239
	H. Madala

    Confirmation in Experimental Mathematics: A Case Study.....259
	William G. Farris and Robert S. Maier

    ``Published six times a year by:
		Complex Systems Publications, Inc.
		P.O. Box 6149
		Champaign, IL 61826
		USA
    
    Subscriptions: $45 (students), $75 (individuals), $250 (institutions),
	Outside North America, add $15 (surface) or $65 (air).''

    
    My only connection with this publication is as a happy subscriber.

						-- Rich
-- 
  ``Read my MIPS -- no new VAXes!!'' -- George Bush after sniffing freon
	    Disclaimer: I speak for myself, except as noted.
UUCP: ...!uunet!dsd.es.com!rthomson			Rich Thomson
Internet: rthomson@dsd.es.com	IRC: _Rich_		PEXt Programmer

From cellular-automata-request@Think.COM  Fri Aug 30 18:57:46 1991
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Date: 30 Aug 91 21:46:09 GMT
From: tom@genie.slhs.udel.edu (tom)
Organization: The Lab Rats
Subject: Re: Tierra (was Re: Genetic algorithms)
Message-Id: <1991Aug30.214609.15744@genie.slhs.udel.edu>
Newsgroups: comp.theory.cell-automata
References: <20084@darkstar.ucsc.edu>, <m0kFf4a-0000XFC@vishnu.reed.edu>
Sender: ca-request@Think.COM
To: ca@Think.COM

In article <m0kFf4a-0000XFC@vishnu.reed.edu> minar@reed.edu (Nelson Minar) writes:
}In article <20084@darkstar.ucsc.edu> vangogh@ucscb.ucsc.edu (vangogh) writes:
}>I saw an article in the San Jose Mercury News this morning about a "computer
}>creature" which piqued my interest.  Would anyone know whether the program
}>described below is accessible via usenet?  Has he published a paper?

}The program mentioned in the paper is called "Tierra", and it is
}written by Thomas Ray, ray@brahms.udel.edu. In fact, he even mentioned
}that the program itself might become available.  Is this true? Anyone
}have it?

the s.j. mercury probably picked up the story from the new york times.
they published an article on tierra in the science section on tue, 8/27.
it has also been in _technology review_, and _science news_ recently.

we are almost ready to distribute the program in a limited way. it will
not be public domain, but tom plans to make it available for research
purposes. this will probably happen in about a week, when he returns from
europe.

-- 
tom@udel.edu                                        ...!{gateway}!udel!tom
tom@genie.slhs.udel.edu           UDel: School of Life and Health Sciences

"Themes were useless; Destiny was here, and the foot pedals were bleeding."

From cellular-automata-request@Think.COM  Fri Aug 30 19:57:09 1991
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Date: 30 Aug 91 21:16:53 GMT
From: cat@acd4.acd.com ( Chris Teegarden (ICCT))
Organization: Applied Computing Devices, Inc., Terre Haute, IN
Subject: Re: Genetic algorithms
Message-Id: <1991Aug30.211653.7206@acd4.acd.com>
Newsgroups: comp.theory.cell-automata
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Sender: ca-request@Think.COM
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I don't know whether or not the source is available, but there is a somewhat
more informative article on his work in a weekly magazine called "Science News".
The issue was for the first or second week of August and the cover story was
about this person's work.

Although the author of the article was not very precise in his descriptions, it
appears that the researcher started with an implementation of CoreWars and
modified it by altering the assembly language instructions and adding
randomizing elements to force evolution.  One of the key details was that some
of the altered instructions would only execute when nearby words contained a
bit pattern (template) that complemented that of the executing instruction.
This allowed competing programs to "sense" each other's proximity.

I was very excited when I read the article as it appears that someone with
my skill set could actually implement something similar.  If anyone could
point me to any material he has published on this work, I would be very
grateful.

-- Chris Teegarden (cat@acd4.acd.com)

From cellular-automata-request@Think.COM  Fri Aug 30 21:57:14 1991
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Date: 31 Aug 91 00:56:36 GMT
From: johng@OCE.ORST.EDU (John A. Gregor)
Organization: College of Oceanography - Oregon State University
Subject: Re: Genetic algorithms
Message-Id: <1991Aug31.005636.5985@usenet@CS.ORST.EDU>
Newsgroups: comp.theory.cell-automata
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Sender: ca-request@Think.COM
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In article <20084@darkstar.ucsc.edu> vangogh@ucscb.ucsc.edu (vangogh) writes:
>
>I saw an article in the San Jose Mercury News this morning about a "computer
>creature" which piqued my interest.  Would anyone know whether the program
>described below is accessible via usenet?  Has he published a paper?

I think this is neat enough to merit a repost in its entirety:

John (all I can say is 'Wow!') G

---------------------------snip-snip-snip-------------------------------

Date: Tue, 5 Mar 91 12:08:44 -0500
From: Thomas Ray <ray@chopin.udel.edu>
Subject: more AL at University of Delaware

The following is an item that I forgot to include with my recent
summary of AL activities at the University of Delaware:

EVOLUTIONARY OPTIMIZATION OF MACHINE CODES - I completed a study of the
effect of the mutation rate on the rate of evolution.  As an index of
the rate of evolution, I used the rate at which self-replicating
machine code programs reduce their size.  The optimal mutation rate was
one that hit about one in four programs per generation.  The programs
reduced themselves from 80 machine instructions to 22 machine
instructions overnight.  There was a five fold decrease in the number
of CPU cycles required for replication.

Below is an abstract that I submitted to the upcoming meeting of the
European Society for Evolutionary Biology, which will meet in Debrecen,
Hungary from September 2 to 6, 1991.  I will submit a separate item
detailing those meetings in a future AL digest.  This is a rather long
abstract, because the program organizers requested two pages.

Synthetic Life: co-evolution in digital organisms.  THOMAS S. RAY.
University of Delaware, Newark, DE, 19716, USA, ray@brahms.udel.edu.
302-451-2753

Synthetic organisms have been created based on a computer metaphor of
organic life in which CPU time is the ``energy'' resource and memory is
the ``material'' resource.  Memory is organized into informational
patterns that exploit CPU time for self-replication.  Mutation
generates new forms, and evolution proceeds by natural selection as
different genotypes compete for CPU time and memory space.  The
creatures are self-replicating computer programs, however, they can not
escape because they run exclusively on a virtual computer in its unique
machine language.  The virtual computer is effectively a containment
facility.

A single rudimentary ancestral ``creature'' has been designed; it is 80
machine instructions long and contains only the code for
self-replication.  This creature examines itself, determines its size
and location in the memory ``soup'', and then copies itself, one
instruction at a time, to another location in the soup.  The ancestral
creature does not interact directly with other individuals, although
there is scrambling competition for access to memory space.

>From a single rudimentary ancestral ``creature'' there have evolved
tens of thousands of self-replicating genotypes of many hundreds of
genome size classes.  Bit flipping mutations cause changes in the
sequence of instructions in the genome, but they do not cause changes
in the size of the genome.  However, mutant genotypes make errors in
their self-examination and replication, resulting in different sized
genomes.  As genetic change generates new genotypes, variants appear
which are able to replicate more rapidly that their ancestors, and
those variants increase in frequency in the soup.

Very quickly there evolve parasites, which are not able to replicate in
isolation because they lack a large portion of the genome.  However,
these parasites search for the missing information, and if they locate
it in a nearby creature, they parasitize the information from the
neighboring genome, thereby effecting their own replication.  This
informational parasitism is a commensal relationship, as it is not
directly detrimental to the host.  However, the parasites do compete
with the hosts for space, and may be superior competitors because they
can more rapidly replicate their smaller genome.  However, their
advantage is frequency dependent.  As the parasites increase in
frequency, the hosts decline, and many parasites fail to locate hosts.
In ecological runs, without genetic change, hosts and parasites
demonstrate Lotka-Volterra cycles.

In some runs, hosts evolve immunity to attack by parasites.  One immune
mechanism that has been worked out is based on the fact that the
creatures only examine themselves once, and rely on retaining the
information on their size and location for all subsequent
replications.  Immune hosts cause their parasites to loose their sense
of self by failing to retain the information on size and location.
Immune hosts function with this forgetful code by re-examining
themselves before each repliction, thus there is a metabolic cost to
the immunity.

When immune hosts appear, they often increase in frequency, devastating
the parasite populations.  In some runs where the community comes to be
dominated by immune hosts, parasites evolve that are resistant to
immunity.  The above mentioned immune mechanism can by circumvented by
parasites which also re-examine themselves before each replication.

Hosts sometimes evolve a response to parasites that goes beyond
immunity, to actual hyper-parasitism.  Hyper-parasites allow themselves
to be parasitized, letting the parasite use their code for a single
replication.  After the first replication, the hyper-parasite deceives
the parasite by replacing the parasite's record of its size and
location with the size and location of the hyper-parasite genome.
Thereafter, the parasite will devote its energetic resources to
replication of the hyper-parastie genome.  This is a highly deleterious
interaction, which drives the parasites to extinction.  The
hyper-parasites are facultative, getting an energy boost when the
parasites are present, but not requiring them for replication.

Evolving in the absence of parasites, hyper-parasites completely
dominate the community, resulting in a relatively uniform community
characterize by a high degree of relationship between individuals.
Under these circumstances, sociality evolves, in the sense that the
creatures evolve into forms which can not replicate in isolation, but
which can only replicate in aggregations.  These colonial creatures
cooperate in the control of the flow of execution of their algorithms.

The cooperative behavior of the social hyper-parasites makes them
vulnerable to a new class of parasites.  These cheaters,
hyper-hyper-parasites, insert themselves between cooperating social
individuals, and momentarily seize control of execution of the
algroithm, just long enough to deceive the social creatures about their
size and location, causing the social creatures to replicate the
genomes of the cheaters.

In a separate experiment, two versions of the ancestral creature were
made, each with a different portion of the genome deleted.  Neither of
these genomes were able to replicate in isolation.  However, when
cultured together, they each parasitize the missing code from the
other, forming an ecologically stable obligate symbiotic relationship.
When genetic change is allowed in the system, a very complex series of
changes follows, ultimately resulting in the merging of the two genomes
into a single self-replicating genome.

The only kind of genetic change that the simulator imposes on the
system is random bit flips in the machine code of the creatures.
However, it turns out that parasites are very sloppy replicators.  They
cause significant recombination and rearrangement of the genomes.  This
spontaneous sexuality is a powerful force for evolutionary change in
the system.

One of the most interesting aspects of this second instance of life is
that the bulk of the evolution is based on adaptation to the biotic
environment rather than the physical environment.  It is co-evolution
that drives the system.

I will make an oral presentation.  I will need an overhead projector,
and two three-pronged power outlets nearby to plug in the computer and
LCD panel.

---------------------------snip-snip-snip-------------------------------
John A. Gregor
College of Oceanography			 E-mail: johng@oce.orst.edu
Oregon State University			Voice #: +1 503 737-3022
Oceanography Admin Bldg. #104		  Fax #: +1 503 737-2064
Corvallis, OR  97331-5503

From cellular-automata-request@Think.COM  Sun Sep  1 00:57:17 1991
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Date: 1 Sep 91 04:42:07 GMT
From: vangogh@ucscb.ucsc.edu (vangogh)
Organization: University of California, Santa Cruz; Open Access Computing
Subject: "Tierra"
Message-Id: <20288@darkstar.ucsc.edu>
Newsgroups: comp.theory.cell-automata
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	Thomas Ray sent me an outline of his work and it looks fascinating.
I'm leery of posting huge files to the net, but if I'm requested to do so I
will.  He's gone out of country before I had a chance to ask him about source
to the program.  Does anyone have a copy they could send off to me?  Thanks.



From cellular-automata-request@Think.COM  Sun Sep  1 10:57:22 1991
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Date: 1 Sep 91 14:11:17 GMT
From: behrens@Informatik.TU-Muenchen.DE (Harry Behrens)
Organization: Technische Universitaet Muenchen, Germany
Subject: Re: Journal of Complex Systems, Volume 5, Number 2 (+address)
Message-Id: <1991Sep1.141117.5266@Informatik.TU-Muenchen.DE>
Newsgroups: comp.theory.cell-automata
References: <1991Aug30.192942.16403@dsd.es.com>
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hi there,
how to i subscribe to that journal? is it also published somewhere in europe
e.g. london? 
if yes please tell me where, how, how much etc..
thanxx in advance.

From cellular-automata-request@Think.COM  Tue Sep  3 17:17:33 1991
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From: vigyan!csa!chandan@shakti.ernet.in
X-Comment: From: vigyan!csa!chandan  - Header Corrected at shakti.ncst.ernet.in

Subject: "Tierra"

vangogh@ucscb.ucsc.edu (vangogh) writes:

>	Thomas Ray sent me an outline of his work and it looks
>fascinating.  I'm leery of posting huge files to the net, but if I'm
>requested to do so I will.

How huge exactly?  I'm worried because my network, ernet.in will
bounce mails larger than 40K, and I'll feel miserable not receiving
this extremely interesting stuff if it is posted on the net!

 -- Chandan


Chandan Haldar                 | Internet:
Doctoral Student               |     csa!chandan@vigyan.ernet.in
Department of Computer Science | UUCP:
	and Automation         | ...uunet!shakti!vigyan!csa!chandan
Indian Institute of Science    |
Bangalore 560 012  INDIA       | Phone:  (91) 0812-344411  x2368

*Standard Caution*: Please do not use the 'reply' option of the mail
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From cellular-automata-request@Think.COM  Tue Sep  3 17:59:14 1991
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Date: Tue, 3 Sep 91 18:32:43 GMT
From: cat@acd4.acd.com ( Chris Teegarden (ICCT))
Organization: Applied Computing Devices, Inc., Terre Haute, IN
Subject: My earlier post about evolving CoreWars programs
Message-Id: <1991Sep3.183243.15118@acd4.acd.com>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM

I noticed that there was some activity in this group this weekend.  Unfortu-
nately, our system administrator deleted it (along with all other postings)
over a day old) to keep from running out of space.  Could some kind soul
please email me all articles for Saturday through Monday (31-Aug through
2-Sep).

If this is too much, could you please forward any postings in response to
my post about the CoreWars based artificial life experiment?

Thanks in advance.

-- Chris Teegarden (cat@acd4.acd.com)

From cellular-automata-request@Think.COM  Tue Sep  3 18:09:26 1991
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Date: Tue, 3 Sep 91 18:10:09 EDT
From: leao@buphy.bu.edu (Joao Leao)
Message-Id: <9109032210.AA20060@buphy.bu.edu>
To: cellular-automata@Think.COM
Subject: Langhton Lecture-Change in Room.


Please note change in room:

------------------------------------------------------------
Department of Physics and the Computational Sciences Center present:
                         
                 "Phase Transitions and Computation"

                         Chris Langton
                         
                     Complex Systems Group
                     Theoretical Division
                  Los Alamos National Laboratory

In studies of Cellular Automata (CA) it has been found that the most
complex dynamics, including the capacity for universal computation, 
is found in the vicinity of a phase transition in the space of CA
rules. This phase transition exhibits many of the properties of 
a second order --- or "critical" --- transition, suggesting a
relationship between universal computation and critical dynamics.


Date:	Friday, September 6 
Time:	12 noon 
Room:   PRB 593	<<<<<<<<<<<************************


Joao Pedro Leao (Artificial Iconoclast and Director of Computer Resources
Artificial Physics Lab * Boston University - Physics Dept. Boston MA 02215)
 	leao@buphy.bu.edu | leao@buphyc.bitnet | BUPHYC::LEAO 
"Well I am sitting here in Tahiti/ I am laying in the sun and sipping a...
...chartreuse tropical drink!/ and I say: I know those Bermuda shorts!..."



From cellular-automata-request@Think.COM  Thu Sep  5 12:58:35 1991
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Date: 5 Sep 91 16:27:18 GMT
From: rdb@scs.carleton.ca (Robert D. Black)
Organization: School of Computer Science, Carleton University, Ottawa, Canada
Subject: Date of next CA conference?
Message-Id: <1991Sep5.162718.21877@cunews.carleton.ca>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
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Does anybody know when the next Conference/Workshop on cellular 
automata will be held?

Thanks!
--
--
Robert Black                               rdb@scs.carleton.ca
School of Computer Science
Carleton University, Ottawa, Canada

From cellular-automata-request@Think.COM  Fri Sep  6 13:05:14 1991
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Date: Fri, 6 Sep 1991 13:07-0400
From: Allan C. Wechsler <ACW@YUKON.SCRC.Symbolics.COM>
Subject: Langhton Lecture-Change in Room.
To: leao@buphy.bu.edu, cellular-automata@Think.COM
In-Reply-To: <9109032210.AA20060@buphy.bu.edu>
Message-Id: <19910906170722.6.ACW@PALLANDO.SCRC.Symbolics.COM>

    Date: Tue, 3 Sep 1991 18:10 EDT
    From: leao@buphy.bu.edu (Joao Leao)


    Please note change in room:

    ------------------------------------------------------------
    Department of Physics and the Computational Sciences Center present:
                         
		     "Phase Transitions and Computation"

			     Chris Langton
                         
			 Complex Systems Group
			 Theoretical Division
		      Los Alamos National Laboratory

    In studies of Cellular Automata (CA) it has been found that the most
    complex dynamics, including the capacity for universal computation, 
    is found in the vicinity of a phase transition in the space of CA
    rules. This phase transition exhibits many of the properties of 
    a second order --- or "critical" --- transition, suggesting a
    relationship between universal computation and critical dynamics.

    Date:	Friday, September 6 
    Time:	12 noon 
    Room:   PRB 593	<<<<<<<<<<<************************

The lecture has already been going an hour as I type this.  Can someone
who attended -- who is attending -- (Gosh, I'll have to write this
sentence in Hopi!) -- post a summary of what was said?

From cellular-automata-request@Think.COM  Fri Sep  6 16:41:29 1991
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Date: Fri, 6 Sep 1991 16:43-0400
From: Allan C. Wechsler <ACW@YUKON.SCRC.Symbolics.COM>
Subject: Re: Universal Turing Machine
To: hoey@AIC.NRL.Navy.Mil, ca@Think.COM
In-Reply-To: <9107310151.AA00402@sun13.aic.nrl.navy.mil>
Message-Id: <19910906204339.8.ACW@PALLANDO.SCRC.Symbolics.COM>

    Date: Tue, 30 Jul 1991 21:51 EDT
    From: hoey@AIC.NRL.Navy.Mil

    minsky@media-lab.media.mit.EDU (Marvin Minsky) writes:

    >Anyway, if you look up the discussion in my book "Computation", you'll
    >find the actual Tag system that obsessed Emil Post: algorithm:

    >  Begin with a string of 0's and 1's.
    >  If the string begins with 0, append "00" to the end.
    >  If the string begins with 1, append "1101" to the end.
    >  Erase the first THREE digits.
    >  Repeat!
 
    >There are various flimsy reasons to suspect that this procedure may be
    >Turing-Universal....

    I replied:

    >A naive probabilistic analysis indicates that the number of 1's will
    >stay about the same, and the number of 0's will converge to the number
    >of 1's.  Is there any particular input for which this behavior seems
    >not to occur?

    Well, I ran this on over 1900 random strings of 100 bits, so I have a
    better idea of what happens.  In 19% of the cases the string became
    empty.  In 81% of the cases, the tag system cycled (the longest cycle
    period seen was 58).  In most cases, one or the other case happened in
    under 1E5 steps, but a few cases went for over 1E6 steps and one went
    for over 6E7 steps before becoming cyclic.

    It seems to me that if this system were universal, I would be likely
    to stumble across one of the ever-growing strings than this.  I
    wouldn't be surprised if this is a terminating tag system, though I
    doubt that anyone will be able to prove it.

    On the other hand, the 1918th string I tried was

    #*00011010011100110000001100010001111100011001010000111101011010-
    11101111111100010100111111001110001110

    which has gone on for over 1E8 steps, so possibly there is something
    to this system.  Still, it hasn't shown any tendency to get steadily
    larger--the length has meandered between 20000 and 40000 for most of
    the history.  I intend to run this a few billion steps--or until it
    terminates, of course.

    Does "Computation" discuss computational experience on the problem, or
    is there any better reference?

    Dan Hoey
    Hoey@AIC.NRL.Navy.Mil

I must confess that as soon as I received your message my mind went into
overdrive, and that I have now been working on this on and off for the
last month.  I don't have any very deep results, but I do have a few
tidbits.

First, allow me to point out that when you run small random Life
patterns (say ten cells square, to be comparable to your 100-bit
starting strings) they nearly all shoot off a few gliders and then
settle down to periodicity within a few thousand generations.  Glider
guns rarely arise spontaneously.  This is not convincing evidence of
non-universality.

To prove universality is an engineering task.  You have to set out to
build patterns with basic useful properties.  It could well be that the
smallest pattern that grows without limit is a million bits long.  Even
if there were an infinite grower with fewer than 100 bits, there might
be only one.

Suppose we have a starting pattern S, 3N bits long.  If we apply the
rule N times, the entire original string is eaten, leaving a new string
which I call the resultant of S or R(S).  I have set myself tomodest
task of characterizing strings S such that S=R(S).  All the ones I have
discovered are made of concatenations of two basic modules: 001101,
which I call "Henry", and 110111010000, which I call "Nancy".

Can you modify your random-search program to halt when it has entered a
repetitive cycle AND the string is a multiple of three long?  According
to my current theory, the string at this stage will simply be a long
chain of Henries and Nancies.  Any exceptions would be of great
theoretical interest.  They would be of one of two basic types: strings
containing other "prime" stable strings besides Henry and Nancy, or
strings with S/=R(S) but S=R(R(S)), or S=R(R(R(S))), and so on.

I hereby earnestly solicit examples of either variety.  If anyone finds
one, please let me know.

By the way, if any primes besides Henry and Nancy exist, then there are
an infinite number.  The shortest such prime must begin

0000000000000000000000000000000000... 

(that's thirty-four zeroes), but between the ninth and tenth zeroes, any
number of copies of the string

011011101110100000

may be inserted.

From cellular-automata-request@Think.COM  Fri Sep  6 16:59:29 1991
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Date: 6 Sep 91 20:40:53 GMT
From: jstravis@bu-pub.bu.edu (John Travis)
Organization: Boston University
Subject: Re: "Tierra"
Message-Id: <89243@bu.edu>
Newsgroups: comp.theory.cell-automata
References: <20288@darkstar.ucsc.edu>
Sender: ca-request@Think.COM
To: ca@Think.COM

In article <20288@darkstar.ucsc.edu>, vangogh@ucscb.ucsc.edu (vangogh) writes:
|> 
|> 
|> 	Thomas Ray sent me an outline of his work and it looks fascinating.
|> I'm leery of posting huge files to the net, but if I'm requested to do so I
|> will.  He's gone out of country before I had a chance to ask him about source
|> to the program.  Does anyone have a copy they could send off to me?  Thanks.

Hi, i wrote the science news article on thomas ray's work.
Last time i talked to him, he was working frantically to get a package
that he could send to researchers. A software company had also contacted
him about a public software package that he could sell. One follow-up
note to my article--the Danish researcher that modified ray's creature
to contain a "suicide" instruction recently found a bug that may nullify
some of his results. nevertheless, the concept of predators seems feasible 
enough that it could be included in tierra.

john travis
jstravi@bu-pub.bu.edu

From cellular-automata-request@Think.COM  Sat Sep  7 04:58:15 1991
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Date: 7 Sep 91 07:17:04 GMT
From: vangogh@ucscb.UCSC.EDU (vangogh)
Organization: University of California, Santa Cruz; Open Access Computing
Subject: Re: "Tierra"
Message-Id: <20536@darkstar.ucsc.edu>
Newsgroups: comp.theory.cell-automata
References: <20288@darkstar.ucsc.edu>, <89243@bu.edu>
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In article <89243@bu.edu> jstravis@bu-pub.bu.edu (John Travis) writes:
>the Danish researcher that modified ray's creature
>to contain a "suicide" instruction recently found a bug that may nullify
>some of his results. nevertheless, the concept of predators seems feasible 
>enough that it could be included in tierra.
>

	Could you elaborate, please?


From cellular-automata-request@Think.COM  Sat Sep  7 23:58:49 1991
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Date: 8 Sep 91 03:26:30 GMT
From: jstravis@bass.bu.edu (John Travis)
Organization: Boston University
Subject: Re: "Tierra"
Message-Id: <89282@bu.edu>
Newsgroups: comp.theory.cell-automata
References: <20288@darkstar.ucsc.edu>, <89243@bu.edu>, <20536@darkstar.ucsc.edu>
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In article <89243@bu.edu> jstravis@bu-pub.bu.edu (John Travis) writes:
>the Danish researcher that modified ray's creature
>to contain a "suicide" instruction recently found a bug that may nullify
>some of his results. nevertheless, the concept of predators seems feasible 
>enough that it could be included in tierra.
>

response:        Could you elaborate, please?

oops, sorry that wasn't in the NYTimes piece I guess. Ray's Tierra has a reaper
program that keeps his memory block partly free so that his "organisms"
gave room for copies of themselves. organisms that are "defective" or ld are
removed by this reaper, but there are no actual predator organisms i.e.
a program-organism doesn't kill others to free up space. a danish
researcher removed the reaper--creating a population crunch--and added
a suicide instruction into the "genome" or instruction set of some of
his program-orgnaisms. These creatures didnot execute the suicide 
instruction and kill themselves; instead parasites executing a host's
code that included this suicide set unwittingly killed themselves--a 
kind of predatory action one might claim. i'm not sure what the bug
was but it seems a neat concept that should work.

john travis
jstravis@bu-pub.bu.edu

From cellular-automata-request@Think.COM  Sun Sep  8 11:59:58 1991
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Date: 8 Sep 91 15:19:27 GMT
From: ray@brahms.udel.edu (Thomas Ray)
Organization: University of Delaware
Subject: Tierra (evolving machine codes)
Message-Id: <24101@brahms.udel.edu>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
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     I have just returned from the European Society for Evolutionary Biology
meetings in Hungary, and have found that there has been some discussion of
my work in this newsgroup.  There is some interest in more information and
in the source code.  I have a manuscript on line (but the figures are in
Generic CADD batch file format) that I can send now to anyone interested.

     I am organizing the source code for distribution. Please realize
that the publicity (Science News Aug. 10, New York Times Aug. 27) was welcome
but unexpected and I just don't have the code ready to go.  I am close to a
release however, and am working on the README file.  I will distribute the
code free of charge only for research purposes.

     I have sent everything but the source code to Robert Chansky who is
planning to post a summary to this group.

     Meanwhile, the papers published or in press are:

Ray, T. S.  1991.  Is it alive, or is it GA?
In: Belew, R. K., and L. B. Booker [eds.], Proceedings of the 1991
International Conference on Genetic Algorithms, 527--534.  San Mateo, CA:
Morgan Kaufmann.

Ray, T. S.  In Press.  An approach to the synthesis of life.
In: Artificial Life II, Santa Fe Institute Studies in the Sciences of
Complexity, vol. XI, (Farmer, J. D., C. Langton, S. Rasmussen, & C. Taylor,
eds).  Redwood City, CA: Addison-Wesley, 1991.

Ray, T. S.  In Press.  Population dynamics of digital organisms.
In: "Artificial Life II Video Proceedings" C.G. Langton (Editor),
Redwood City, CA: Addison Wesley, 1991.

Ray, T. S.  In Press.  ``Evolution and optimization of digital
organisms.'' In: 1990 IBM Supercomputing Competition: Large Scale
Computing Analysis and Modeling Conference Proceedings, edited by H. Brown.
Cambridge, MA: MIT Press.

     I've heard a rumor that the Addison Wesley book is out, but I haven't
seen it.  Although I don't have a paper in it, you might be interested in the
following book which is available now:

Langton, Christopher G. [ed.].  1989.  Artificial life: proceedings of an
interdisciplinary workshop on the synthesis and simulation of living systems.
Vol. VI in the series: Santa Fe Institute studies in the sciences of
complexity.  Addison-Wesley.

This work will also be presented in the following upcoming seminars:

National Science Foundation, Washington, September 20, 1991

University of Maryland, Biology, October 29, 1991

Texas Instruments, Dallas, November 21, 1991

Harvard University, Biology (Lewontin's lab), December 2, 1991

Boston University, Computational Sciences Center, December 3, 1991

University of Massachusetts Boston, Biology, December 5, 1991

Yale University, Biology, December 6, 1991

Stony Brook, Department of Ecology and Evolution, December 11, 1991

University of Arizona, Ecology & Evolutionary Biology, March 10, 1992

There is an Artificial Life mailing list.  It is distributed as a digest
to avoid chaos.  You may subscribe to the list by sending a message to:

                   alife-request@cognet.ucla.edu

and you may post to the list by sending a message to:

  		      alife@cognet.ucla.edu

                             Tom Ray
                       University of Delaware
                  School of Life & Health Sciences
                      Newark, Delaware  19716
                        ray@brahms.udel.edu
                         302-451-2281 (FAX)
                            302-451-2753

From cellular-automata-request@Think.COM  Sun Sep  8 20:58:32 1991
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Date: 9 Sep 91 00:17:42 GMT
From: vangogh@ucscb.UCSC.EDU (vangogh)
Organization: University of California, Santa Cruz; Open Access Computing
Subject: Re: Tierra (evolving machine codes)
Message-Id: <20562@darkstar.ucsc.edu>
Newsgroups: comp.theory.cell-automata
References: <24101@brahms.udel.edu>
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In article <24101@brahms.udel.edu> ray@brahms.udel.edu (Thomas Ray) writes:
>     I have sent everything but the source code to Robert Chansky who is
>planning to post a summary to this group.
>

	I am?  Well, anyway, he's sent me a few articles, and I in turn have
been sending them off to quite a few folks.  If anyone else would like a copy
of the longest article (a superset, I think, of the others) in two parts,
please send mail to the address below (note that that mail address is not
the one I am posting from).


From cellular-automata-request@Think.COM  Mon Sep  9 01:59:02 1991
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Date: 9 Sep 91 05:24:33 GMT
From: vangogh@ucscb.UCSC.EDU (vangogh)
Organization: University of California, Santa Cruz; Open Access Computing
Subject: Re: Tierra (evolving machine codes)
Message-Id: <20574@darkstar.ucsc.edu>
Newsgroups: comp.theory.cell-automata
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In article <20562@darkstar.ucsc.edu> vangogh@ucscb.UCSC.EDU (vangogh) writes:
>In article <24101@brahms.udel.edu> ray@brahms.udel.edu (Thomas Ray) writes:
>

	Of course, when I said 'below' I was referring to this message right
here, which should contain the .signature of my work account:
-- 

####  #       #   #    # #    # # #    #  ###   #  ##    #### # # ### ## # # ###
#   # #      # #  ##   # ##   # # ##   # #   #  # #      #    # # #   # # #   #
#   # #     #   # # #  # # #  # # # #  # #      #  ##    ##   # # ##  ##  #   #
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#     ##### #   # #    # #    # # #    #  ###   #  ##    ####  #  ### # # #   #
Robert Chansky         uunet.uu.net!ucscc!sco.com!robertc, robertc@sco.com

From cellular-automata-request@Think.COM  Mon Sep  9 17:59:09 1991
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Date: 9 Sep 91 19:37:47 GMT
From: robertc@sco.COM (Robert Chansky)
Organization: The Santa Cruz Operation, Inc.
Subject: Tierra articles
Message-Id: <14038@scolex.sco.COM>
Newsgroups: comp.theory.cell-automata
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	Well, after getting about two dozen requests for the article I've
decided to post it instead and save my sanity (and possibly my job).  I will
post it in two parts which will hopefully keep it from bouncing to less
accessible sites.  If it's not in the next two articles, please wait a day or
two before asking me personally, as I understand large postings are given
a somewhat lower priority.  But if you don't get it, you are welcome to ask me. 

Costing the net hundreds if not thousands of dollars,
-- 
####  #       #   #    # #    # # #    #  ###   #  ##    #### # # ### ## # # ###
#   # #      # #  ##   # ##   # # ##   # #   #  # #      #    # # #   # # #   #
#   # #     #   # # #  # # #  # # # #  # #      #  ##    ##   # # ##  ##  #   #
####  #     ##### #  # # #  # # # #  # # # ###  #    #   #    # # #   # # #   #
#     #     #   # #   ## #   ## # #   ## #   #  #    #   #    # # #   # # #   #
#     ##### #   # #    # #    # # #    #  ###   #  ##    ####  #  ### # # #   #
Robert Chansky         uunet.uu.net!ucscc!sco.com!robertc, robertc@sco.com

From cellular-automata-request@Think.COM  Mon Sep  9 18:00:51 1991
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Date: 9 Sep 91 19:40:21 GMT
From: robertc@sco.COM (Robert Chansky)
Organization: The Santa Cruz Operation, Inc.
Subject: Tierra Pt II
Message-Id: <14040@scolex.sco.COM>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
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0045aaa is a ``metabolic parasite''.  Its genome does not include the
copy procedure, however it executes the copy procedure code of
a normal host, such as the ancestor.  In an environment favoring small
creatures, 0045aaa has a competitive advantage over the ancestor, however, the
relationship is density dependent.  When the hosts become scarce, most of
the parasites are not within the search limit of a copy procedure, and are
not able to reproduce.  Their calls to the copy procedure fail and generate
errors, causing them to rise to the top of the reaper queue and die.
When the parasites die off, the host population rebounds.  Hosts and parasites
cultured together demonstrate Lotka-Volterra population cycling (Lotka [25];
Volterra [35]; Wilson \& Bossert [36]).

A number of experiments have been conducted to explore the factors affecting
diversity of size classes in these communities.  Competitive exclusion trials
were conducted with a series of self-replicating (non-parasitic) genotypes
of different size classes.  The experimental soups were initially inoculated
with one individual of each size.  A genotype of size 79 was tested against a
genotype of size 80, and then against successively larger size classes.  The
interactions were observed by plotting the population of the size 79 class
on the $x$ axis, and the population of the other size class on the $y$ axis.
Sizes 79 and 80 were found to be competitively matched such that neither was
eliminated from the soup.  They quickly entered a stable cycle, which exactly
repeated a small orbit.  The same general pattern was found in the interaction
between sizes 79 and 81.

When size 79 was tested against size 82, they initially entered a stable
cycle, but after about 4 million instructions they shook out of stability
and the trajectory became chaotic with an attractor that was symmetric about
the diagonal (neither size showed any advantage).  This pattern was repeated
for the next several size classes, until size 90, where a marked asymmetry of
the chaotic attractor was evident, favoring size 79.  The run of size 79
against size 93 showed a brief stable period of about a million instructions,
which then moved to a chaotic phase without an attractor, which spiraled
slowly down until size 93 became extinct, after an elapsed time of about 6
million instructions.

An interesting exception to this pattern was the interaction between size 79
and size 89.  Size 89 is considered to be a ``metabolic cripple'', because
although it is capable of self-replicating, it executes about 40\% more
instructions than normal to replicate.  It was eliminated in competition
with size 79, with no loops in the trajectory, after an elapsed time of
under one million instructions.

In an experiment to determine the effects of the presence of parasites on
community diversity, a community consisting of twenty size classes of hosts
was created and allowed to run for 30 million instructions, at which time only
the eight smallest size classes remained.  The same community was then
regenerated, but a single genotype (0045aaa) of parasite was also introduced.
After 30 million instructions, 16 size classes remained, including the
parasite.  This seems to be an example of a ``keystone'' parasite effect
(Paine [28]).

Symbiotic relationships are also possible.  The ancestor was manually dissected
into two creatures, one of size 46 which contained only the code for
self-examination and the copy loop, and one of size 64 which contained only
the code for self-examination and the copy procedure (Figure 3).  Neither
could replicate when cultured alone, but when cultured together, they both
replicated, forming a stable mutualistic relationship.  It is not known if
such relationships have evolved spontaneously.

\LP
\bf 3.4 EVOLUTIONARY OPTIMIZATION\rm
\eLP

In order to compare the process of evolution between runs of the simulator,
a simple objective quantitative measure of evolution is needed.  One such
measure is the degree to which creatures improve their efficiency through
evolution.  This provides not only an objective measure of progress in
evolution, but also sheds light on the potential application of synthetic
life systems to the problem of the optimization of machine code.

The efficiency of the creature can be indexed in two ways: the size of the
genome, and the number of CPU cycles needed to execute one replication.
Clearly, smaller genomes can be replicated with less CPU time, however,
during evolution, creatures also decrease the ratio of instructions executed
in one replication, to genome size.  The number of instructions executed per
instruction copied, drops substantially.

Figure 4 shows the changes in genome size over a time period of 500 million
instructions executed by the system, for eight sets of mutation rates
differing by factors of two.  Mutation rates are measured in terms of 1 in
N individuals being affected by a mutation in each generation.  At the highest
two sets of rates tested, one and two, either each (one) or one-half (two)
of the individuals are hit by mutation in each generation.  At these rates
the system is unstable.  The genomes melt under the heat of the high mutation
rates.  The community often dies out, although some runs survived the 500
million instruction runs used in this study.  The next lower rate, four,
yields the highest rate of optimization without the risk of death of the
community.  At the five lower mutation rates, 8, 16, 32, 64 and 128,
we see successively lower rates of optimization.

Additional replicates were made of the runs at the mutation rate of four
(Fig.\ 5).  The replicates differ only in the seed of the
random number generator, all other parameters being identical.  These runs
vary in some details such as whether progress is continuous and gradual, or
comes in bursts.  Also, each run decreases to a size limit which it can not
proceed past even if it is allowed to run much longer.  However, different
runs reach different plateaus of efficiency.  The smallest limiting genome
size seen has been 22 instructions, while other runs reached limits of 27
and 30 instructions.  Evidently, the system can reach a local optima from
which it can not easily evolve to the global optima.

The increase in efficiency of the replicating algorithms is even greater than
the decrease in the size of the code.  The ancestor is 80 instructions
long and requires 839 CPU cycles to replicate.  The creature of size 22
only requires 146 CPU cycles to replicate, a 5.75--fold difference in
efficiency.  The algorithm of one of these creatures is listed in Appendix D.

Although optimization of the algorithm is maximized at the highest mutation
rate that does not cause instability, ecological interactions appear to be
richer at slightly lower mutation rates.  At the rates of eight or 16, we
find the diversity of coexisting size classes to be the greatest, and to
persist the longest.  The smaller size classes tend to be various forms of
parasites, thus a diversity of size classes indicates a rich ecology.

An example of even greater optimization is illustrated in Appendix E and
discussed above in section 3.1.1.8.  Unrolling of the loop results in a
loop which uses 18 CPU cycles to copy three instructions, or six CPU
cycles executed per instruction copied, compared to 10 for the ancestor.
The creature of size 22 also uses six CPU cycles per instruction copied.
However, the creature of Appendix E uses three extra CPU cycles per loop
to compensate for a separate adaptation that allows it to double its share
of CPU time from the global pool.  Without this compensation it would use only
five CPU cycles per instruction copied.

\LP
\rule[6pt]{6.5in}{1pt}
\large \bf 4 SUMMARY\rm \normalsize
\eLP

\LP
\bf 4.1 GENERAL BEHAVIOR OF THE SYSTEM\rm
\eLP

Once the soup is full of replicating creatures, individuals are initially
short lived, generally reproducing only once before dying, thus individuals
turn over very rapidly.  More slowly, there appear new genotypes of size 80,
and then new size classes.  There are changes in the genetic composition
of each size class, as new mutants appear, some of which increase significantly
in frequency, eventually replacing the original genotype.  The size classes
which dominate the community also change through time, as new size classes
appear, some of which competitively exclude sizes present earlier.
Once the community becomes diverse, there is a greater variance in
the longevity and fecundity of individuals.

In addition to an increase in the raw diversity of genotypes and genome sizes,
there is an increase in the ecological diversity.  Obligate commensal
parasites evolve, which are not capable of self-replication in isolated
culture, but which can replicate when cultured with normal (self-replicating)
creatures.  These parasites execute some parts of the code of their hosts,
but cause them no direct harm, except as competitors.  Some potential hosts
have evolved immunity to the parasites, and some parasites have evolved to
circumvent this immunity.

In addition, facultative hyper-parasites have evolved, which can
self-replicate in isolated culture, but when subjected to parasitism, subvert
the parasites energy metabolism to augment their own reproduction.
Hyper-parasites drive parasites to extinction, resulting in complete
domination of the communities.  The relatively high degrees of genetic
relatedness within the hyper-parasite dominated communities leads to the
evolution of sociality in the sense of creatures that can only replicate
when they occur in aggregations.  These social aggregations are then invaded
by hyper-hyper-parasite cheaters.

Mutations and the ensuing replication errors lead to an increasing diversity
of sizes and genotypes of self-replicating creatures in the soup.  Within
the first 100 million instructions of elapsed time, the soup evolves to
a state in which about a dozen more-or-less persistent size classes coexist.
The relative abundances and specific list of the size classes varies over time.
Each size class consists of a number of distinct genotypes which also vary
over time.

The rate of evolution increases with the mutation rate until the system
becomes unstable, and the community dies at rates above one mutation per four
generations.  Ecological interactions are richer and more sustained at
slightly lower rates, one mutation per eight or 16 generations.  At mutation
rates of one per four generations, under selection for small sizes, creatures
will optimize to a genome size in the 22 to 30 instruction size range within
as little as 300 million instructions of elapsed time.  Each of these runs
will reach a local optima which it evidently cannot escape from, although it
may not be the global optima.

\LP
\bf 4.2 INCREASING COMPLEXITY\rm
\eLP

The unrolled loop (section 3.1.1.8) is an example of the ability of evolution
to produce an increase in complexity, gradually over a long period of time.
The interesting thing about the loop unrolling optimization technique is that
it requires more complex code.  The resulting creature has a genome size of 36,
compared to its ancestor of size 80, yet it has packed a much more complex
algorithm into less than half the space (Appendix E).

This is a classic example of intricate design in evolution.  One wonders how
it could have arisen through random bit flips, as every component of the code
must be in place in order for the algorithm to function.  Yet the code
includes a classic mix of apparent intelligent design, and the chaotic hand
of evolution.  The optimization technique is a very clever one invented by
humans, yet it is implemented in a mixed up but functional style that no human
would use (unless perhaps very intoxicated).

\LP
\bf 4.3 EMERGENCE\rm
\eLP

The ``physical'' environment presented by the simulator is quite simple,
consisting of the energy resource (CPU time) doled out rather uniformly by
the time slicer, and memory space which is completely uniform and always
available.  In light of the nature of the physical environment, the implicit
fitness function would presumably favor the evolution of creatures which are
able to replicate with less CPU time, and this does in fact occur.  However,
much of the evolution in the system consists of the creatures discovering ways
to exploit one-another.  The creatures invent their own fitness functions
through adaptation to their biotic (``living'') environment.  These ecological
interactions are not programmed into the system, but emerge spontaneously as
the creatures discover each other and invent their own games.

In the Tierran world, creatures which initially
do not interact, discover means to exploit one another, and in response, means
to avoid exploitation.  The original fitness landscape of the ancestor
consists only of the efficiency parameters of the replication algorithm, in
the context of the properties of the reaper and slicer queues.  When by
chance, genotypes appear that exploit other creatures, selection acts to
perfect the mechanisms of exploitation, and mechanisms of defense to that
exploitation.  The original fitness landscape was based only on adaptations
of the organism to its physical environment.  The
new fitness landscape retains those features, but adds to it adaptations to
the biotic environment, the other creatures.  Because the fitness landscape
includes an ever increasing realm of adaptations to other creatures which
are themselves evolving, it can facilitate an auto-catalytic increase in
complexity and diversity of organisms.

Evolutionary theory suggests that adaptation to the biotic environment (other
organisms) rather than to the physical environment is the primary force
driving the auto-catalytic diversification of organisms (Stanley [34]).  It
is encouraging to discover that the process has already begun in the Tierran
world.  It is worth noting that the results presented here are based on
evolution of the first creature that I designed, written in the first
instruction set that I designed.  Comparison to the creatures that have
evolved shows that the one I designed is not a particularly clever one.  Also,
the instruction set that the creatures are based on is certainly not very
powerful (apart from those special features incorporated to enhance its
evolvability).  It would appear then that it is rather easy to create life.
Evidently, virtual life is out there, waiting for us to provide environments
in which it may evolve.

\LP
\bf 4.4 SYNTHETIC BIOLOGY\rm
\eLP

One of the most uncanny of evolutionary phenomena is the ecological convergence
of biota living on different continents or in different epochs.  When a
lineage of organisms undergoes an adaptive radiation (diversification),
it leads to an array of relatively stable ecological forms.  The specific
ecological forms are often recognizable from lineage to lineage.  For example
among dinosaurs, the \it Pterosaur\rm, \it Triceratops\rm,
\it Tyrannosaurus \rm and \it Ichthyosaur \rm
are ecological parallels respectively, to the bat, rhinoceros, lion and
porpoise of modern mammals.  Similarly, among modern placental mammals, the
gray wolf, flying squirrel, great anteater and common mole are ecological
parallels respectively, to the Tasmanian wolf, honey glider, banded anteater
and marsupial mole of the marsupial mammals of Australia.

Given these evidently powerful convergent forces, it should perhaps not be
surprising that as adaptive radiations proceed among digital organisms, we
encounter recognizable ecological forms, in spite of the fundamentally
distinct physics and chemistry on which they are based.  Ideally, comparisons
should be made among organisms of comparable complexity.  It may not be
appropriate to compare viruses to mammals.  Unfortunately, the organic
creatures most comparable to digital organisms, the RNA creatures, are no
longer with us.  Since digital organisms are being compared to modern organic
creatures of much greater complexity, ecological comparisons must be made in
the broadest of terms.

Trained biologists will tend to view synthetic life in the same terms that
they have come to know organic life.  Having been trained as an ecologist
and evolutionist, I have seen in my synthetic communities, many of the
ecological and evolutionary properties that are well known from natural
communities.  Biologists trained in other specialties will likely observe
other familiar properties.  It seems that what we see is what we know.  It
is likely to take longer before we appreciate the unique properties of these
new life forms.

\LP
\bf 4.5 APPLICATIONS\rm
\eLP

The phenomenon of synthetic life is so new that it is impossible to know
what its practical applications might be.  Perhaps the most immediate
application is as a technique for the optimization of machine codes.

A new version of the Tierran language is currently under development which
will retain those features of the language that make it evolvable, while
at the same time expanding its functionality to the point that is should
be possible to develop cross-assemblers between it and real assembler
languages.  Application code written and compiled to run on real machines
could be cross-assembled into the new Tierran language.  Each procedure could
then be inserted into the genome of a creature.  Creatures could be rewarded
with CPU time in proportion to the efficacy and efficiency of the evolving
inserted code.  In this way, artificial selection would lead to the
optimization of the inserted code, which could then be cross-assembled back
into the real machine code.

If this proved to be practical, it would be worthwhile to render the Tierran
virtual instruction set in silicon, thereby greatly accelerating the process.
At present, maximum optimization can be achieved in a few hours of running
the Tierran virtual computer.  If a real computer were based on the
architectural principals of the Tierran computer, such optimization could
be achieved in minutes.  If machine code could evolve that quickly, then
there is the possibility of using it as a generative process in addition to
an optimization procedure.  There may also be some potential application in
the areas of machine learning or adaptive programming.

Another interesting possibility is the study of evolving communities of
digital organisms as a source of new paradigms for the programming of
massively parallel machines.  It is already known that digital organisms
have spontaneously evolved linear programming tricks used by humans
(like unrolling loops).  The kinds of ecological interactions already
observed in digital communities could in another light, be viewed as
optimization techniques for parallel programming (e.g., the sharing of
code fragments).  However, these interactions evolve in a ``jungle''-like
environment where most interactions are of an adversarial nature.  When
evolving large parallel application programs, the most viable model would
be a multi-cellular one, where many cells would cooperate on a common
problem.  A multi-cellular model is under development.  In the end, evolution
may prove to be the best method of programming massively parallel machines.

\LP
\rule[6pt]{6.5in}{1pt}
\large \bf 5 ACKNOWLEDGMENT\rm \normalsize
\eLP

I thank Marc Cygnus, Robert Eisenberg, Doyne
Farmer, Walter Fontana, Stephanie Forrest, Chris Langton, Dan
Pirone, Stephen Pope, and Steen Rasmussen, for their discussions or readings
of the manuscripts.  Contribution No.\ 150 from the Ecology Program, School
of Life and Health Sciences, University of Delaware.

\LP
\rule[6pt]{6.5in}{1pt}
\large \bf 6 REFERENCES\rm \normalsize
\eLP

\XP

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[3] Bagley, R. J., Farmer, J. D., Kauffman, S. A., Packard, N. H., Perelson,
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[4] Barbieri, M.  \it The semantic theory of evolution\rm .  London:
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[6] Cohen, F.  \it Computer viruses: theory and experiments\rm .
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[9] Denning, P. J.  ``Computer viruses.''  \it Amer.\ Sci.\ \bf 76 \rm
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[10] Dewdney, A. K.  ``Computer recreations:  In the game called Core
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[11] Dewdney, A. K.  ``Computer recreations:  A core war bestiary of
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[12] Dewdney, A. K.  ``Computer recreations:  Exploring the field of
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[13] Dewdney, A. K.  ``Computer recreations:  A program called MICE
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[14] Dewdney, A. K.  ``Of worms, viruses and core war.''
\it Sci.\ Amer.\ \bf 260 \rm (1989): 110--113.

[15] Eldredge, N. \& Gould, S. J.  ``Punctuated equilibria: an alternative
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[16] Farmer, J. D., Kauffman, S. A., \& Packard, N. H.  ``Autocatalytic
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[17] Farmer, J. D. \& Belin, A.  ``Artificial life: the
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[21] Holland, J. H.  ``Studies of the spontaneous emergence of
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[22] Langton, C. G.  ``Studying artificial life with cellular automata.''
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[23] Langton, C. G.  ``Virtual state machines in cellular automata.''
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[24] Langton, C. G.  ``Artificial life.''  In: \it Artificial life: proceedings
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[25] Lotka, A. J.  \it Elements of physical biology\rm .  Baltimore: Williams
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[26] Minsky, M. L.  \it Computation: finite and infinite machines\rm .
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[28] Paine, R. T.  ``Food web complexity and species diversity.''
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[29] Packard, N. H.  ``Intrinsic adaptation in a simple model for
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[30] Pattee, H. H.  ``Simulations, realizations, and theories of life.''
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[33] Spafford, E. H., Heaphy, K. A. \& Ferbrache, D. J.  \it Computer
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[34] Stanley, S. M.  ``An ecological theory for the sudden origin
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Sci.\ \bf 70 \rm (1973): 1486--1489.

[35] Volterra, V.  ``Variations and fluctuations of the number of individuals
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R. N. Chapman.  New York: McGraw-Hill, 1926, 409--448.

[36] Wilson, E. O. \& Bossert, W. H.  \it A primer of population
biology\rm .  Stamford, Conn: Sinauer Associates, 1971.
\eXP

\newpage
\addtocounter{page}{1}

\LP
\bf Figure 1.  Metabolic flow chart for the ancestor, parasite, hyper-parasite,
and their interactions: \rm ax, bx and cx refer to CPU registers where location
and size information are stored.  [ax] and [bx] refer to locations in the
soup indicated by the values in the ax and bx registers.  Patterns such as
1101 are complementary templates used for addressing.  Arrows outside of boxes
indicate jumps in the flow of execution of the programs.  The dotted-line
arrows indicate flow of execution between creatures.  The parasite lacks the
copy procedure, however, if it is within the search limit of the copy
procedure of a host, it can locate, call and execute that procedure, thereby
obtaining the information needed to complete its replication.  The host is
not adversely affected by this informational parasitism, except through
competition with the parasite, which is a superior competitor.  Note that
the parasite calls the copy procedure of its host with the expectation that
control will return to the parasite when the copy procedure returns.  However,
the hyper-parasite jumps out of the copy procedure rather than returning,
thereby seizing control from the parasite.  It then proceeds to reset the CPU
registers of the parasite with the location and size of the hyper-parasite,
causing the parasite to replicate the hyper-parasite genome thereafter.

\newpage
\addtocounter{page}{1}

\bf Figure 2.  Metabolic flow chart for social hyper-parasites, their
associated hyper-hyper-parasite cheaters, and their interactions. \rm  Symbols
are as described for Fig.\ 1.  Horizontal dashed lines indicate the boundaries
between individual creatures.  On both the left and right, above the dashed
line at the top of the figure is the lowermost fragment of a
social-hyper-parasite.  Note (on the left) that neighboring social
hyper-parasites cooperate in returning the flow of execution to the beginning
of the creature for self-re-examination.  Execution jumps back to the end of
the creature above, but then falls off the end of the creature without
executing any instructions of consequence, and enters the top of the creature
below.  On the right, a cheater is inserted between the two
social-hyper-parasites.  The cheater captures control of execution when it
passes between the social individuals.  It sets the CPU registers with its own
location and size, and then skips over the self-examination step when it
returns control of execution to the social creature below.

\newpage
\addtocounter{page}{1}

\bf Figure 3.  Metabolic flow chart for obligate symbionts and their
interactions. \rm  Symbols are as described for Fig.\ 1.  Neither creature is
able to self-replicate in isolation.  However, when cultured together, each
is able to replicate by using information provided by the other.

\newpage
\addtocounter{page}{1}

\bf Figure 4.  Evolutionary optimization at eight sets of mutation rates. \rm
In each run, the three mutation rates: move mutations (copy error), flaws
and background mutations (cosmic rays) are set relative to the generation
time.  In each case, the background mutation rate is the lowest, affecting
a cell once in twice as many generations as the move mutation rate.  The
flaw rate is intermediate, affecting a cell once in 1.5 times as many
generations as the move mutation rate.  For example in one run, the move
mutation will affect a cell line on the average once every 4 generations,
the flaw will occur once every 6 generations, and the background mutation
once every 8 generations.  The horizontal axis shows elapsed time in
hundreds of millions of instructions executed by the system.  The vertical
axis shows genome size in instructions.  Each point indicates the first
appearance of a new genotype which crossed the abundance thresholds of
either 2\% of the population of cells in the soup, or occupation of 2\% of
the memory.  The number of generations per move mutation is indicated by
a number in the upper right hand corner of each graph.

\newpage
\addtocounter{page}{3}

\bf Figure 5.  Variation in evolutionary optimization under constant
conditions. \rm  Based on a mutation rate of four generations per move
mutation, all other parameters as in Fig.\ 4.  The plots are otherwise
as described for Fig.\ 4.

\newpage
\addtocounter{page}{1}

Table 1:  Genebank.  Table of numbers of size classes in the genebank.  Left
column is size class, right column is number of self-replicating genotypes
of that size class.  305 sizes, 29,275 genotypes.
\eLP

\begin{verbatim}
0034 1       0092 362     0150 2       0205 5       0418 1       5213 2
0041 2       0093 261     0151 1       0207 3       0442 10      5229 4
0043 12      0094 241     0152 2       0208 2       0443 1       5254 1
0044 7       0095 211     0153 1       0209 1       0444 61      5888 36
0045 191     0096 232     0154 2       0210 9       0445 1       5988 1
0046 7       0097 173     0155 3       0211 4       0456 2       6006 2
0047 5       0098 92      0156 77      0212 4       0465 6       6014 1
0048 4       0099 117     0157 270     0213 5       0472 6       6330 1
0049 8       0100 77      0158 938     0214 47      0483 1       6529 1
0050 13      0101 62      0159 836     0218 1       0484 8       6640 1
0051 2       0102 62      0160 3229    0219 1       0485 3       6901 5
0052 11      0103 27      0161 1417    0220 2       0486 9       6971 1
0053 4       0104 25      0162 174     0223 3       0487 2       7158 2
0054 2       0105 28      0163 187     0226 2       0493 2       7293 3
0055 2       0106 19      0164 46      0227 7       0511 2       7331 1
0056 4       0107 3       0165 183     0231 1       0513 1       7422 70
0057 1       0108 8       0166 81      0232 1       0519 1       7458 1
0058 8       0109 2       0167 71      0236 1       0522 6       7460 7
0059 8       0110 8       0168 9       0238 1       0553 1       7488 1
0060 3       0111 71      0169 15      0240 3       0568 6       7598 1
0061 1       0112 19      0170 99      0241 1       0578 1       7627 63
0062 2       0113 10      0171 40      0242 1       0581 3       7695 1
0063 2       0114 3       0172 44      0250 1       0582 1       7733 1
0064 1       0115 3       0173 34      0251 1       0600 1       7768 2
0065 4       0116 5       0174 15      0260 2       0683 1       7860 25
0066 1       0117 3       0175 22      0261 1       0689 1       7912 1
0067 1       0118 1       0176 137     0265 2       0757 6       8082 3
0068 2       0119 3       0177 13      0268 1       0804 2       8340 1
0069 1       0120 2       0178 3       0269 1       0813 1       8366 1
0070 7       0121 60      0179 1       0284 16      0881 6       8405 5
0071 5       0122 9       0180 16      0306 1       0888 1       8406 2
0072 17      0123 3       0181 5       0312 1       0940 2       8649 2
0073 2       0124 11      0182 27      0314 1       1006 6       8750 1
0074 80      0125 6       0184 3       0316 2       1016 1       8951 1
0075 56      0126 11      0185 21      0318 3       1077 5       8978 3
0076 21      0127 1       0186 9       0319 2       1116 1       9011 3
0077 28      0130 3       0187 3       0320 23      1186 1       9507 3
0078 409     0131 2       0188 11      0321 5       1294 7       9564 3
0079 850     0132 5       0190 20      0322 21      1322 7       9612 1
0080 7399    0133 2       0192 12      0330 1       1335 1       9968 1
0081 590     0134 7       0193 4       0342 5       1365 11     10259 31
0082 384     0135 1       0194 4       0343 1       1631 1      10676 1
0083 886     0136 1       0195 11      0351 1       1645 3      11366 5
0084 1672    0137 1       0196 19      0352 3       2266 1      11900 1
0085 1531    0138 1       0197 2       0386 1       2615 2      12212 2
0086 901     0139 2       0198 3       0388 2       2617 9      15717 3
0087 944     0141 6       0199 35      0401 3       2671 7      16355 1
0088 517     0143 1       0200 1       0407 1       3069 3      17356 3
0089 449     0144 4       0201 84      0411 22      4241 1      18532 1
0090 543     0146 1       0203 1       0412 3       5101 15     23134 14
0091 354     0149 1       0204 1       0416 1       5157 9
\end{verbatim}

\newpage

\baselineskip = 14pt
\LP
\bf APPENDIX A\rm
\eLP

Structure definition to implement the Tierra virtual CPU.
The complete source code for the Tierra Simulator can be obtained by
contacting the author by email.

\begin{verbatim}
struct cpu {  /* structure for registers of virtual cpu */
    int   ax;  /* address register */
    int   bx;  /* address register */
    int   cx;  /* numerical register */
    int   dx;  /* numerical register */
    char  fl;  /* flag */
    char  sp;  /* stack pointer */
    int   st[10];  /* stack */
    int   ip;  /* instruction pointer */
    } ;
\end{verbatim}

\LP
\bf APPENDIX B\rm
\eLP

Abbreviated code for implementing the CPU cycle of the Tierra Simulator.

\begin{verbatim}
void main(void)
{   get_soup();
    life();
    write_soup();
}

void life(void) /* doles out time slices and death */
{   while(inst_exec_c < alive)  /* control the length of the run */
    {   time_slice(this_slice); /* this_slice is current cell in queue */
        incr_slice_queue(); /* increment this_slice to next cell in queue */
        while(free_mem_current < free_mem_prop * soup_size)
            reaper(); /* if memory is full to threshold, reap some cells */
    }
}

void time_slice(int  ci)
{   Pcells  ce; /* pointer to the array of cell structures */
    char    i;  /* instruction from soup */
    int     di; /* decoded instruction */
    int     j, size_slice;
    ce = cells + ci;
    for(j = 0; j < size_slice; j++)
    {   i = fetch(ce->c.ip); /* fetch instruction from soup, at address ip */
        di = decode(i);      /* decode the fetched instruction */
        execute(di, ci);     /* execute the decoded instruction */
        increment_ip(di,ce); /* move instruction pointer to next instruction */
        system_work(); /* opportunity to extract information */
    }
}

void execute(int  di, int  ci)
{   switch(di)
    {   case 0x00: nop_0(ci);    break; /* no operation */
        case 0x01: nop_1(ci);    break; /* no operation */
        case 0x02: or1(ci);      break; /* flip low order bit of cx, cx ^= 1 */
        case 0x03: shl(ci);      break; /* shift left cx register, cx <<= 1 */
        case 0x04: zero(ci);     break; /* set cx register to zero, cx = 0 */
        case 0x05: if_cz(ci);    break; /* if cx==0 execute next instruction */
        case 0x06: sub_ab(ci);   break; /* subtract bx from ax, cx = ax - bx */
        case 0x07: sub_ac(ci);   break; /* subtract cx from ax, ax = ax - cx */
        case 0x08: inc_a(ci);    break; /* increment ax, ax = ax + 1 */
        case 0x09: inc_b(ci);    break; /* increment bx, bx = bx + 1 */
        case 0x0a: dec_c(ci);    break; /* decrement cx, cx = cx - 1 */
        case 0x0b: inc_c(ci);    break; /* increment cx, cx = cx + 1 */
        case 0x0c: push_ax(ci);  break; /* push ax on stack */
        case 0x0d: push_bx(ci);  break; /* push bx on stack */
        case 0x0e: push_cx(ci);  break; /* push cx on stack */
        case 0x0f: push_dx(ci);  break; /* push dx on stack */
        case 0x10: pop_ax(ci);   break; /* pop top of stack into ax */
        case 0x11: pop_bx(ci);   break; /* pop top of stack into bx */
        case 0x12: pop_cx(ci);   break; /* pop top of stack into cx */
        case 0x13: pop_dx(ci);   break; /* pop top of stack into dx */
        case 0x14: jmp(ci);      break; /* move ip to template */
        case 0x15: jmpb(ci);     break; /* move ip backward to template */
        case 0x16: call(ci);     break; /* call a procedure */
        case 0x17: ret(ci);      break; /* return from a procedure */
        case 0x18: mov_cd(ci);   break; /* move cx to dx, dx = cx */
        case 0x19: mov_ab(ci);   break; /* move ax to bx, bx = ax */
        case 0x1a: mov_iab(ci);  break; /* move instruction at address in bx
                                           to address in ax */
        case 0x1b: adr(ci);      break; /* address of nearest template to ax */
        case 0x1c: adrb(ci);     break; /* search backward for template */
        case 0x1d: adrf(ci);     break; /* search forward for template */
        case 0x1e: mal(ci);      break; /* allocate memory for daughter cell */
        case 0x1f: divide(ci);   break; /* cell division */
    }
    inst_exec_c++;
}
\end{verbatim}
\newpage
\LP
\bf APPENDIX C\rm
\eLP

Assembler source code for the ancestral creature.

\begin{verbatim}
genotype: 80 aaa  origin: 1-1-1990  00:00:00:00  ancestor
parent genotype: human
1st_daughter:  flags: 0  inst: 839  mov_daught: 80
2nd_daughter:  flags: 0  inst: 813  mov_daught: 80

nop_1    ; 01   0 beginning template
nop_1    ; 01   1 beginning template
nop_1    ; 01   2 beginning template
nop_1    ; 01   3 beginning template
zero     ; 04   4 put zero in cx
or1      ; 02   5 put 1 in first bit of cx
shl      ; 03   6 shift left cx
shl      ; 03   7 shift left cx, now cx = 4
         ;        ax =                 bx =
         ;        cx = template size   dx =
mov_cd   ; 18   8 move template size to dx
         ;        ax =                 bx =
         ;        cx = template size   dx = template size
adrb     ; 1c   9 get (backward) address of beginning template
nop_0    ; 00  10 compliment to beginning template
nop_0    ; 00  11 compliment to beginning template
nop_0    ; 00  12 compliment to beginning template
nop_0    ; 00  13 compliment to beginning template
         ;        ax = start of mother + 4   bx =
         ;        cx = template size         dx = template size
sub_ac   ; 07  14 subtract cx from ax
         ;        ax = start of mother   bx =
         ;        cx = template size     dx = template size
mov_ab   ; 19  15 move start address to bx
         ;        ax = start of mother   bx = start of mother
         ;        cx = template size     dx = template size
adrf     ; 1d  16 get (forward) address of end template
nop_0    ; 00  17 compliment to end template
nop_0    ; 00  18 compliment to end template
nop_0    ; 00  19 compliment to end template
nop_1    ; 01  20 compliment to end template
         ;        ax = end of mother   bx = start of mother
         ;        cx = template size   dx = template size
inc_a    ; 08  21 to include dummy statement to separate creatures
sub_ab   ; 06  22 subtract start address from end address to get size
         ;        ax = end of mother    bx = start of mother
         ;        cx = size of mother   dx = template size
nop_1    ; 01  23 reproduction loop template
nop_1    ; 01  24 reproduction loop template
nop_0    ; 00  25 reproduction loop template
nop_1    ; 01  26 reproduction loop template
mal      ; 1e  27 allocate memory for daughter cell, address to ax
         ;        ax = start of daughter    bx = start of mother
         ;        cx = size of mother       dx = template size
call     ; 16  28 call template below (copy procedure)
nop_0    ; 00  29 copy procedure compliment
nop_0    ; 00  30 copy procedure compliment
nop_1    ; 01  31 copy procedure compliment
nop_1    ; 01  32 copy procedure compliment
divide   ; 1f  33 create independent daughter cell
jmp      ; 14  34 jump to template below (reproduction loop, above)
nop_0    ; 00  35 reproduction loop compliment
nop_0    ; 00  36 reproduction loop compliment
nop_1    ; 01  37 reproduction loop compliment
nop_0    ; 00  38 reproduction loop compliment
if_cz    ; 05  39 this is a dummy instruction to separate templates
         ;        begin copy procedure
nop_1    ; 01  40 copy procedure template
nop_1    ; 01  41 copy procedure template
nop_0    ; 00  42 copy procedure template
nop_0    ; 00  43 copy procedure template
push_ax  ; 0c  44 push ax onto stack
push_bx  ; 0d  45 push bx onto stack
push_cx  ; 0e  46 push cx onto stack
nop_1    ; 01  47 copy loop template
nop_0    ; 00  48 copy loop template
nop_1    ; 01  49 copy loop template
nop_0    ; 00  50 copy loop template
mov_iab  ; 1a  51 move contents of [bx] to [ax]
dec_c    ; 0a  52 decrement cx
if_cz    ; 05  53 if cx == 0 perform next instruction, otherwise skip it
jmp      ; 14  54 jump to template below (copy procedure exit)
nop_0    ; 00  55 copy procedure exit compliment
nop_1    ; 01  56 copy procedure exit compliment
nop_0    ; 00  57 copy procedure exit compliment
nop_0    ; 00  58 copy procedure exit compliment
inc_a    ; 08  59 increment ax
inc_b    ; 09  60 increment bx
jmp      ; 14  61 jump to template below (copy loop)
nop_0    ; 00  62 copy loop compliment
nop_1    ; 01  63 copy loop compliment
nop_0    ; 00  64 copy loop compliment
nop_1    ; 01  65 copy loop compliment
if_cz    ; 05  66 this is a dummy instruction, to separate templates
nop_1    ; 01  67 copy procedure exit template
nop_0    ; 00  68 copy procedure exit template
nop_1    ; 01  69 copy procedure exit template
nop_1    ; 01  70 copy procedure exit template
pop_cx   ; 12  71 pop cx off stack
pop_bx   ; 11  72 pop bx off stack
pop_ax   ; 10  73 pop ax off stack
ret      ; 17  74 return from copy procedure
nop_1    ; 01  75 end template
nop_1    ; 01  76 end template
nop_1    ; 01  77 end template
nop_0    ; 00  78 end template
if_cz    ; 05  79 dummy statement to separate creatures
\end{verbatim}
\newpage
\LP
\bf APPENDIX D\rm
\eLP

Assembler source code for the smallest self-replicating creature.

\begin{verbatim}
genotype: 0022abn  parent genotype: 0022aak
1st_daughter:  flags: 1  inst: 146  mov_daught: 22  breed_true: 1
2nd_daughter:  flags: 0  inst: 142  mov_daught: 22  breed_true: 1
InstExecC: 437  InstExec: 625954  origin: 662865379  Wed Jan  2 20:16:19 1991
MaxPropPop: 0.1231  MaxPropInst: 0.0568

nop_0   ; 00   0
adrb    ; 1c   1 find beginning
nop_1   ; 01   2
divide  ; 1f   3 fails the first time it is executed
sub_ac  ; 07   4
mov_ab  ; 19   5
adrf    ; 1d   6 find end
nop_0   ; 00   7
inc_a   ; 08   8 to include final dummy statement
sub_ab  ; 06   9 calculate size
mal     ; 1e  10
push_bx ; 0d  11 save beginning address on stack in order to `return' there
nop_0   ; 00  12 top of copy loop
mov_iab ; 1a  13
dec_c   ; 0a  14
if_cz   ; 05  15
ret     ; 17  16 jump to beginning, address saved on stack
inc_a   ; 08  17
inc_b   ; 09  18
jmpb    ; 15  19 bottom of copy loop (6 instructions executed per loop)
nop_1   ; 01  20
mov_iab ; 1a  21 dummy statement to terminate template
\end{verbatim}

\newpage
\LP
\bf APPENDIX E\rm
\eLP

Assembler code for the central copy loop of the ancestor
(80aaa) and decendant after fifteen billion instructions (72etq).  Within
the loop, the ancestor does each of the following operations once: copy
instruction (51), decrement cx (52), increment ax (59) and increment bx (60).
The decendant performs each of the following operations three times within
the loop: copy instruction (15, 22, 26), increment ax (20, 24, 31) and
increment bx (21, 25, 32).  The decrement cx operation occurs five times
within the loop (16, 17, 19, 23, 27).  Instruction 28 flips the low order
bit of the cx register.  Whenever this latter instruction is reached, the
value of the low order bit is one, so this amounts to a sixth instance of
decrement cx.  This means that there are two decrements for every increment.
The reason for this is related to another adaptation of this creature.  When
it calculates its size, it shifts left (12) before allocating space for the
daughter (13).  This has the effect of allocating twice as much space as
is actually needed to accomodate the genome.  The genome of the creature
is 36 instructions long, but it allocates a space of 72 instructions.
This occurred in an environment where the slice size was set equal to the
size of the cell.  In this way the creatures were able to garner twice as
much energy.  However, they had to compliment this change by doubling the
number of decrements in the loop.

\newpage

\begin{verbatim}
nop_1    ; 01  47 copy loop template      COPY LOOP OF 80AAA
nop_0    ; 00  48 copy loop template
nop_1    ; 01  49 copy loop template
nop_0    ; 00  50 copy loop template
mov_iab  ; 1a  51 move contents of [bx] to [ax] (copy instruction)
dec_c    ; 0a  52 decrement cx
if_cz    ; 05  53 if cx = 0 perform next instruction, otherwise skip it
jmp      ; 14  54 jump to template below (copy procedure exit)
nop_0    ; 00  55 copy procedure exit compliment
nop_1    ; 01  56 copy procedure exit compliment
nop_0    ; 00  57 copy procedure exit compliment
nop_0    ; 00  58 copy procedure exit compliment
inc_a    ; 08  59 increment ax (point to next instruction of daughter)
inc_b    ; 09  60 increment bx (point to next instruction of mother)
jmp      ; 14  61 jump to template below (copy loop)
nop_0    ; 00  62 copy loop compliment
nop_1    ; 01  63 copy loop compliment
nop_0    ; 00  64 copy loop compliment
nop_1    ; 01  65 copy loop compliment (10 instructions executed per loop)


shl     ; 000 03  12 shift left cx        COPY LOOP OF 72ETQ
mal     ; 000 1e  13 allocate daughter cell
nop_0   ; 000 00  14 top of loop
mov_iab ; 000 1a  15 copy instruction
dec_c   ; 000 0a  16 decrement cx
dec_c   ; 000 0a  17 decrement cx
jmpb    ; 000 15  18 junk
dec_c   ; 000 0a  19 decrement cx
inc_a   ; 000 08  20 increment ax
inc_b   ; 000 09  21 increment bx
mov_iab ; 000 1a  22 copy instruction
dec_c   ; 000 0a  23 decrement cx
inc_a   ; 000 08  24 increment ax
inc_b   ; 000 09  25 increment bx
mov_iab ; 000 1a  26 copy instruction
dec_c   ; 000 0a  27 decrement cx
or1     ; 000 02  28 flip low order bit of cx
if_cz   ; 000 05  29 if cx == 0 do next instruction
ret     ; 000 17  30 exit loop
inc_a   ; 000 08  31 increment ax
inc_b   ; 000 09  32 increment bx
jmpb    ; 000 15  33 go to top of loop (6 instructions per copy)
nop_1   ; 000 01  34 bottom of loop    (18 instructions executed per loop)
\end{verbatim}

\end{document}


-- 
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#     ##### #   # #    # #    # # #    #  ###   #  ##    ####  #  ### # # #   #
Robert Chansky         uunet.uu.net!ucscc!sco.com!robertc, robertc@sco.com

From cellular-automata-request@Think.COM  Mon Sep  9 18:01:15 1991
Received: by mail.think.com; Mon, 9 Sep 91 18:01:23 -0400
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Date: 9 Sep 91 19:39:29 GMT
From: robertc@sco.COM (Robert Chansky)
Organization: The Santa Cruz Operation, Inc.
Subject: Tierra article -- Pt I
Message-Id: <14039@scolex.sco.COM>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM


    Here is the file I've been sending out to those who've asked:

-------------------------------------------------------------------------------

He sent me a few other articles, but this one is kind of a conglomeration of
them both.  At the bottom of part 2 you will find source to the creatures
and pseudo-source to the program that runs them.

This is all in LaTex, and aside from a few snide comments I don't really know
what to make of it.  

enjoy,
Rob


\documentstyle[12pt]{article}

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\textwidth 6.5in
\textfloatsep 30pt plus 3pt minus 6pt
\parskip 7.5pt plus 1pt minus 1pt
\oddsidemargin 0in
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% Hanging Paragraph
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% Left Justified Paragraph
\def\LP{\par\begingroup\parindent 0in\everypar{\hangindent 0in}}
\def\eLP{\par\endgroup}

\begin{document}
\thispagestyle{empty}

\LP
\bf Thomas S. Ray\rm \\
School of Life \& Health Sciences, University of Delaware, Newark, Delaware
19716,\\
ray@brahms.udel.edu\\
\rule[6pt]{6.5in}{1pt}
\Large \bf Evolution and Optimization of Digital Organisms\rm \normalsize\\
\rule[6pt]{6.5in}{2pt}
\eLP

Digital organisms have been synthesized based on a computer metaphor of
organic life in which CPU time is the ``energy'' resource and memory is
the ``material'' resource.  Memory is organized into informational ``genetic''
patterns that exploit CPU time for self-replication.  Mutation generates
new forms, and evolution proceeds by natural selection as different
``genotypes'' compete for CPU time and memory space.  In addition, new
genotypes appear which exploit other ``creatures'' for informational or
energetic resources.

The digital organisms are self-replicating computer programs, however,
they can not escape because they run exclusively on a virtual computer
in its unique machine language.  From a single ancestral ``creature''
there have evolved tens of thousands of self-replicating genotypes of
hundreds of genome size classes.  Parasites evolved, then creatures that
were immune to parasites, and then parasites that could circumvent the
immunity.  Hyper-parasites evolved which subvert parasites to their own
reproduction and drive them to extinction.  The resulting genetically
uniform communities evolve sociality in the sense of creatures that can
only reproduce in cooperative aggregations, and these aggregations are
then invaded by cheating hyper-hyper-parasites.

Diverse ecological communities have emerged.  These digital communities
have been used to experimentally study ecological and evolutionary processes:
e.g., competitive exclusion and coexistance, symbiosis, host/parasite density
dependent population regulation, the effect of parasites in enhancing
community diversity, evolutionary arms races, punctuated equilibrium, and
the role of chance and historical factors in evolution.  It is possible to
extract information on any aspect of the system without disturbing it, from
phylogeny or community structure through time to the ``genetic makeup'' and
``metabolic processes'' of individuals.  Digital life demonstrates the
power of the computational approach to science as a complement to the
traditional approaches of experiment, and theory based on analysis through
calculus and differential equations.

Optimization experiments have shown that freely evolving digital organisms
can optimize their algorithms by a factor of 5.75 in a few hours of real
time.  In addition, evolution discovered the optimization technique of
``unrolling the loop''.  Evolution may provide a new method for the
optimization or generation of application programs.  This method may
prove particularly useful for programming massively parallel machines.

\LP
\rule[6pt]{6.5in}{1pt}
evolution, ecology, artificial life, synthetic life, emergence,
self-replication, diversity, adaptation, coevolution, optimization
\eLP

\newpage

% \baselineskip = 20pt

\LP
\bf Thomas S. Ray\rm \\
School of Life \& Health Sciences, University of Delaware, Newark, Delaware
19716,\\
ray@brahms.udel.edu\\
\rule[6pt]{6.5in}{1pt}
\Large \bf Evolution and Optimization of Digital Organisms\rm \normalsize\\
\rule[6pt]{6.5in}{2pt}
\vspace{6cm}

\begin{quote}
Marcel, a mechanical chessplayer... his exquisite 19th-century brainwork
--- the human art it took to build which has been flat lost, lost as the
dodo bird ...  But where inside Marcel is the midget Grandmaster, the
little Johann Allgeier?  where's the pantograph, and the magnets?  Nowhere.
Marcel really is a mechanical chessplayer.  No fakery inside to give
him any touch of humanity at all.\\
\hspace*{2in}--- Thomas Pynchon, \it Gravity's Rainbow\rm .
\end{quote}

\large \bf 1 INTRODUCTION\rm \normalsize
\eLP

Ideally, the science of biology should embrace all forms of life.  However
in practice, it has been restricted to the study of a single instance of
life, life on earth.  Life on earth is very diverse, but it is presumably
all part of a single phylogeny.  Because biology is based on a sample size
of one, we can not know what features of life are peculiar to earth, and
what features are general, characteristic of all life.  A truly comparative
natural biology would require inter-planetary travel, which is light
years away.  The ideal experimental evolutionary biology would involve
creation of multiple planetary systems, some essentially identical,
others varying by a parameter of interest, and observing them for billions
of years.

A practical alternative to an inter-planetary or mythical biology is to
create synthetic life in a computer.  The objective is not necessarily
to create life forms that would serve as models for the study of natural
life, but rather to create radically different life forms, based on a
completely different physics and chemistry, and let these life forms
evolve their own phylogeny, leading to whatever forms are natural to their
unique physical basis.  These truly independent instances of life may
then serve as a basis for comparison, to gain some insight into what is
general and what is peculiar in biology.  Those aspects of life that prove
to be general enough to occur in both natural and synthetic systems can then
be studied more easily in the synthetic system.  ``Evolution in a bottle''
provides a valuable tool for the experimental study of evolution and ecology.

The intent of this work is to synthesize rather than simulate life.  This
approach starts with hand crafted organisms already capable of replication
and open-ended evolution, and aims to generate increasing diversity and
complexity in a parallel to the Cambrian explosion.  To state such a goal
leads to semantic problems, because life must be defined in a way that does
not restrict it to carbon based forms.  It is unlikely that there could be
general agreement on such a definition, or even on the proposition that life
need not be carbon based.  Therefore, I will simply state my conception of
life in its most general sense.  I would consider a system to be living if
it is self-replicating, and capable of open-ended evolution.  Synthetic life
should self-replicate, and evolve structures or processes that were not
designed-in or pre-conceived by the creator (Pattee [30]; Cariani [5]).

Core Wars programs, computer viruses, and worms (Cohen [6]; Dewdney [10,
11, 13, 14]; Denning [9]; Rheingold [32]; Spafford et al. [33]) are capable
of self-replication, but fortunately, not evolution.  It is unlikely that
such programs will ever become fully living, because they are not likely
to be able to evolve.

Most evolutionary simulations are not open-ended.  Their potential is limited
by the structure of the model, which generally endows each individual with a
genome consisting of a set of pre-defined genes, each of which may exist
in a pre-defined set of allelic forms (Holland [20]; Dewdney [12]; Dawkins
[7, 8]; Packard [29]; Ackley \& Littman [1]).  The object being evolved
is generally a data structure representing the genome, which the simulator
program mutates and/or recombines, selects, and replicates according to
criteria designed into the simulator.  The data structures do not contain the
mechanism for replication, they are simply copied by the simulator if they
survive the selection phase.

Self-replication is critical to synthetic life because without it, the
mechanisms of selection must also be pre-determined by the simulator.  Such
artificial selection can never be as creative as natural selection.  The
organisms are not free to invent their own fitness functions.  Freely
evolving creatures will discover means of mutual exploitation and
associated implicit fitness functions that we would never think of.
Simulations constrained to evolve with pre-defined genes, alleles and fitness
functions are dead ended, not alive.

The approach presented here does not have such constraints.  Although the
model is limited to the evolution of creatures based on sequences of machine
instructions, this may have a potential comparable to evolution based on
sequences of organic molecules.  Sets of machine instructions similar to
those used in the Tierra Simulator have been shown to be capable of
``universal computation'' (Aho et al. [2]; Minsky [26]; Langton [24]).
This suggests that evolving machine codes should be able to generate any
level of complexity.

Other examples of the synthetic approach to life can be seen in the work of
Holland [21], Farmer et al.\ [16], Langton [22], Rasmussen et al.\
[31], and Bagley et al.\ [3].  A characteristic these efforts
generally have in common is that they parallel the origin of life event by
attempting to create prebiotic conditions from which life may emerge
spontaneously and evolve in an open ended fashion.

While the origin of life is generally recognized as an event of the first
order, there is another event in the history of life that is less well known
but of comparable significance: the origin of biological diversity and
macroscopic multicellular life during the Cambrian explosion 600 million
years ago.  This event involved a riotous diversification of life forms.
Dozens of phyla appeared suddenly, many existing only fleetingly, as
diverse and sometimes bizarre ways of life were explored in a relative
ecological void (Gould [18]; Morris [27]).

The work presented here aims to parallel the second major event in the
history of life, the origin of diversity.  Rather than attempting to create
prebiotic conditions from which life may emerge, this approach involves
engineering over the early history of life to design complex evolvable
organisms, and then attempting to create the conditions that will set off
a spontaneous evolutionary process of increasing diversity and complexity
of organisms.  This work represents a first step in this direction, creating
an artificial world which may roughly parallel the RNA world of
self-replicating molecules (still falling far short of the Cambrian explosion).

The approach has generated rapidly diversifying communities of self-replicating
organisms exhibiting open-ended evolution by natural selection.  From a single
rudimentary ancestral creature containing only the code for self-replication,
interactions such as parasitism, immunity, hyper-parasitism, sociality and
cheating have emerged spontaneously.  This paper presents a methodology and
some first results.

Apart from its value as a tool for the study or teaching of ecology and
evolution, synthetic life may have commercial applications.  Evolution of
machine code provides a new approach to the design and optimization of
computer programs.  In an analogy to genetic engineering, pieces of
application code may be inserted into the genomes of digital organisms,
and then evolved to new functionality or greater efficiency.

\LP
\rule[6pt]{6.5in}{1pt}

\begin{quote}
Here was a world of simplicity and certainty...
a world based on the one and zero of life and
death.  Minimal, beautiful.  The patterns of lives and deaths....
weightless, invisible chains of electronic presence or absence.  If
patterns of ones and zeros were ``like'' patterns of human lives and
deaths, if everything about an individual could be represented in a
computer record by a long string of ones and zeros, then what kind of
creature would be represented by a long string of lives and deaths?
It would have to be up one level at least --- an angel, a minor god,
something in a UFO.\\
\hspace*{2in} --- Thomas Pynchon, \it Vineland\rm .
\end{quote}

\large \bf 2 METHODS\rm \normalsize

\bf 2.1 THE METAPHOR\rm
\eLP

Organic life is viewed as utilizing energy, mostly derived
from the sun, to organize matter.  By analogy, digital life can be
viewed as using CPU (central processing unit) time, to organize memory.
Organic life evolves through natural selection as individuals compete for
resources (light, food, space, etc.) such that genotypes which leave the
most descendants increase in frequency.  Digital life evolves through the
same process, as replicating algorithms compete for CPU time and memory
space, and organisms evolve strategies to exploit one another.  CPU time is
thought of as the analog of the energy resource, and memory as the analog
of the spatial resource.

The memory, the CPU and the computer's operating system are viewed as elements
of the ``abiotic'' (physical) environment.  A ``creature'' is then designed
to be specifically adapted to the features of the computational environment.
The creature consists of a self-replicating assembler language program.
Assembler languages are merely mnemonics for the machine codes that are
directly executed by the CPU.  These machine codes have the characteristic
that they directly invoke the instruction set of the CPU and services provided
by the operating system.

All programs, regardless of the language they are written in, are converted
into machine code before they are executed.  Machine code is the natural
language of the machine, and machine instructions are viewed by this
author as the ``atomic units'' of computing.  It is felt that machine
instructions provide the most natural basis for an artificial chemistry
of creatures designed to live in the computer.

In the biological analogy, the machine instructions are considered to be
more like the amino acids than the nucleic acids, because they are
``chemically active''.  They actively manipulate bits, bytes, CPU registers,
and the movements of the instruction pointer (see below).  The digital
creatures discussed here are entirely constructed of machine instructions.
They are considered analogous to creatures of the RNA world, because the
same structures bear the ``genetic'' information and carry out the
``metabolic'' activity.

A block of RAM memory (random access memory, also known as ``main'' or
``core'' memory) in the computer is designated as a ``soup'' which can
be inoculated with creatures.  The ``genome'' of the creatures consists of
the sequence of machine instructions that make up the creature's
self-replicating algorithm.  The prototype creature consists of 80 machine
instructions, thus the size of the genome of this creature is 80 instructions,
and its ``genotype'' is the specific sequence of those 80 instructions
(Appendix C).

\LP
\bf 2.2 THE VIRTUAL COMPUTER --- TIERRA SIMULATOR\rm
\eLP

The computers we use are general purpose computers, which means, among
other things, that they are capable of emulating through software, the
behavior of any other computer that ever has been built or that could be
built (Aho et al. [2]; Minsky [26]; Langton [24]).  We can utilize
this flexibility to design a computer that would be especially hospitable
to synthetic life.

There are several good reasons why it is not wise to attempt to synthesize
digital organisms that exploit the machine codes and operating systems of
real computers.  The most urgent is the potential threat of natural evolution
of machine codes leading to virus or worm type of programs that could
be difficult to eradicate due to their changing ``genotypes''.  This potential
argues strongly for creating evolution exclusively in programs that run only
on virtual computers and their virtual operating systems.  Such programs
would be nothing more than data on a real computer, and therefore would
present no more threat than the data in a data base or the text file of a
word processor.

Another reason to avoid developing digital organisms in the machine code of
a real computer is that the artificial system would be tied to the hardware
and would become obsolete as quickly as the particular machine it was
developed on.  In contrast, an artificial system developed on a virtual
machine could be easily ported to new real machines as they become available.

A third issue, which potentially makes the first two moot, is that
the machine languages of real machines are not designed to be evolvable,
and in fact might not support significant evolution.  Von Neuman type
machine languages are considered to be ``brittle'', meaning that the
ratio of viable programs to possible programs is virtually zero.  Any
mutation or recombination event in a real machine code is almost certain
to produce a non-functional program.  The problem of brittleness can be
mitigated by designing a virtual computer whose machine code is designed
with evolution in mind.  Farmer \& Belin [17] have suggested that
overcoming this brittleness and ``Discovering how to make such self-replicating
patterns more robust so that they evolve to increasingly more complex states
is probably the central problem in the study of artificial life.''

The work described here takes place on a virtual computer known as Tierra
(Spanish for Earth).  Tierra is a parallel computer of the MIMD (multiple
instruction, multiple data) type, with a processor (CPU) for each creature.
Parallelism is imperfectly emulated by allowing each CPU to execute a small
time slice in turn.  Each CPU of this virtual computer contains two address
registers, two numeric registers, a flags register to indicate error
conditions, a stack pointer, a ten word stack, and an instruction pointer.
Each virtual CPU is implemented via the C structure listed in Appendix A.
Computations performed by the Tierran CPUs are probabilistic due to flaws
that occur at a low frequency (see Mutation below).

The instruction set of a CPU typically performs simple arithmetic
operations or bit manipulations, within the small set of registers contained
in the CPU.  Some instructions move data between the registers in the CPU,
or between the CPU registers and the RAM (main) memory.  Other instructions
control the location and movement of an ``instruction pointer'' (IP).  The
IP indicates an address in RAM, where the machine code
of the executing program (in this case a digital organism) is located.

The CPU perpetually performs a fetch-decode-execute-increment\_IP
cycle:  The machine code instruction currently addressed by the IP
is fetched into the CPU, its bit pattern is decoded to determine which
instruction it corresponds to, and the instruction is executed.  Then
the IP is incremented to point sequentially to the next position in RAM,
from which the next instruction will be fetched.  However, some instructions
like JMP, CALL and RET directly manipulate the IP, causing execution to
jump to some other sequence of instructions in the RAM.  In the Tierra
Simulator this CPU cycle is implemented through the time\_slice routine
listed in Appendix B.  

\LP
\bf 2.3 THE TIERRAN LANGUAGE\rm
\eLP

Before attempting to set up a synthetic life system, careful thought must
be given to how the representation of a programming language affects its
adaptability in the sense of being robust to genetic operations such as
mutation and recombination.  The nature of the virtual computer is defined
in large part by the instruction set of its machine language.  The approach
in this study has been to loosen up the machine code in a ``virtual
bio-computer'', in order to create a computational system based on a hybrid
between biological and classical von Neumann processes.

In developing this new virtual language, which is called ``Tierran'', close
attention has been paid to the structural and functional properties of the
informational system of biological molecules: DNA, RNA and proteins.  Two
features have been borrowed from the biological world which are considered
to be critical to the evolvability of the Tierran language.

First, the instruction set of the Tierran language has been defined to be
of a size that is the same order of magnitude as the genetic
code.  Information is encoded into DNA through 64 codons, which are
translated into 20 amino acids.  In its present manifestation, the Tierran
language consists of 32 instructions, which can be represented by five bits,
\it operands included\rm.

Emphasis is placed on this last point because some instruction sets are
deceptively small.  Some versions of the redcode language of Core Wars
(Dewdney [10, 13]; Rasmussen et al. [31]) for example are defined to have
ten operation codes.  It might appear on the surface then that the
instruction set is of size ten.  However, most of the ten instructions have
one or two operands.  Each operand has four addressing modes, and then an
integer.  When we consider that these operands are embedded into the machine
code, we realize that they are in fact a part of the instruction set, and
this set works out to be about $10^{11}$ in size.  Similarly, RISC machines
may have only a few opcodes, but they probably all use 32 bit instructions,
so from a mutational point of view, they really have $2^{32}$ instructions.
Inclusion of numeric operands will make any instruction set extremely large
in comparison to the genetic code.

In order to make a machine code with a truly small instruction set, we must
eliminate numeric operands.  This can be accomplished by allowing the CPU
registers and the stack to be the only operands of the instructions.  When
we need to encode an integer for some purpose, we can create it in a numeric
register through bit manipulations: flipping the low order bit and shifting
left.  The program can contain the proper sequence of bit flipping and shifting
instructions to synthesize the desired number, and the instruction set need
not include all possible integers.

A second feature that has been borrowed from molecular biology in the design
of the Tierran language is the addressing mode, which is called ``address
by template''.  In most machine codes, when a piece of data is addressed, or
the IP jumps to another piece of code, the exact numeric address of the data
or target code is specified in the machine code.  Consider that in the
biological system by contrast, in order for protein molecule A in the cytoplasm
of a cell to interact with protein molecule B, it does not
specify the exact coordinates where B is located.  Instead, molecule A
presents a template on its surface which is complementary to some surface on
B.  Diffusion brings the two together, and the complementary conformations
allow them to interact.

Addressing by template is illustrated by the Tierran JMP (jump) instruction.
Each JMP instruction is followed by a sequence of NOP (no-operation)
instructions, of which there are two kinds: NOP\_0 and NOP\_1.  Suppose we
have a piece of code with five instruction in the following order:
JMP NOP\_0 NOP\_0 NOP\_0 NOP\_1.  The system will search outward in both
directions from the JMP instruction looking for the nearest occurrence of the
complementary pattern: NOP\_1 NOP\_1 NOP\_1 NOP\_0.  If the pattern is found,
the instruction pointer will move to the end of the complementary pattern
and resume execution.  If the pattern is not found, an error condition (flag)
will be set and the JMP instruction will be ignored (in practice, a limit
is placed on how far the system may search for the pattern).

The Tierran language is characterized by two unique features: a truly small
instruction set without numeric operands, and addressing by template.
Otherwise, the language consists of familiar instructions typical of most
machine languages, e.g., MOV, CALL, RET, POP, PUSH etc.  The complete
instruction set is listed in Appendix B.

\LP
\bf 2.4 THE TIERRAN OPERATING SYSTEM\rm
\eLP

The Tierran virtual computer needs a virtual operating system that will be
hospitable to digital organisms.  The operating system will determine the
mechanisms of interprocess communication, memory allocation, and the
allocation of CPU time among competing processes.  Algorithms will
evolve so as to exploit these features to their advantage.  More than being
a mere aspect of the environment, the operating system together with the
instruction set will determine the
topology of possible interactions between individuals, such as the ability
of pairs of individuals to exhibit predator-prey, parasite-host or 
mutualistic relationships.

\LP
\bf 2.4.1 Memory Allocation --- Cellularity\rm
\eLP

The Tierran computer operates on a block of RAM of the real computer which
is set aside for the purpose.  This block of RAM is referred to as the
``soup''.  In most of the work described here the soup consisted of about
60,000 bytes, which can hold the same number of Tierran machine instructions.
Each ``creature'' occupies some block of memory in this soup.

Cellularity is one of the fundamental properties of organic life, and can
be recognized in the fossil record as far back as 3.6 billion years (Barbieri
[4]).  The cell is the original individual, with the cell membrane defining
its limits and preserving its chemical integrity.  An analog to the cell
membrane is needed in digital organisms in order to preserve the integrity of
the informational structure from being disrupted easily by the activity of
other organisms.  The need for this can be seen in Artificial Life models
such as cellular automata where virtual state machines pass through one
another (Langton [22, 23]), or in core wars type simulations where
coherent structures demolish one another when they come into contact
(Dewdney [10, 13]; Rasmussen et al. [31]).

Tierran creatures are considered to be cellular in the sense that they are
protected by a ``semi-permeable membrane'' of memory allocation.  The Tierran
operating system provides memory allocation services.  Each creature has
exclusive write privileges within its allocated block of memory.  The ``size''
of a creature is just the size of its allocated block (e.g., 80 instructions).
This usually corresponds to the size of the genome.  This ``membrane'' is
described as ``semi-permeable'' because
while write privileges are protected, read and execute privileges are not.
A creature may examine the code of another creature, and even execute it,
but it can not write over it.  Each creature may have exclusive write
privileges in at most two blocks of memory: the one that it is born with
which is referred to as the ``mother cell'', and a second block which it
may obtain through the execution of the MAL (memory allocation) instruction.
The second block, referred to as the ``daughter cell'', may be used to grow
or reproduce into.

When Tierran creatures ``divide'', the mother cell loses write privileges
on the space of the daughter cell, but is then free to allocate another
block of memory.  At the moment of division, the daughter cell is given
its own instruction pointer, and is free to allocate its own second block of
memory.

\LP
\bf 2.4.2 Time Sharing --- The Slicer\rm
\eLP

The Tierran operating system must be multi-tasking (or parallel) in order for
a community of individual creatures to live in the soup simultaneously.  The
system doles out small slices of CPU time to each creature in the soup in turn.
The system maintains a circular queue called the ``slicer queue''.  As each
creature is born, a virtual CPU is created for it, and it enters the slicer
queue just ahead of its mother, which is the active creature at that time.
Thus the newborn will be the last creature in the soup to get another time
slice after the mother, and the mother will get the next slice after its
daughter.  As long as the slice size is small relative to the generation
time of the creatures, the time sharing system causes the world to approximate
parallelism.  In actuality, we have a population of virtual CPUs, each of
which gets a slice of the real CPU's time as it comes up in the queue.

The number of instructions to be executed in each time slice may be set
proportional to the size of the genome of the creature being executed, raised
to a power.  If the ``slicer power'' is equal to one, then the slicer is size
neutral, the probability of an instruction being executed does not depend on
the size of the creature in which it occurs.  If the power is greater than one,
large creatures get more CPU cycles per instruction than small creatures.
If the power is less than one, small creatures get more CPU cycles per
instruction.  The power determines if selection favors large or small
creatures, or is size neutral.  A constant slice size selects for small
creatures. 

\LP
\bf 2.4.3 Mortality --- The Reaper\rm
\eLP

Self-replicating creatures in a fixed size soup would rapidly fill the
soup and lock up the system.  To prevent this from occurring, it is
necessary to include mortality.  The Tierran operating system includes a
``reaper'' which begins ``killing'' creatures from a queue when the memory
fills to some specified level (e.g., 80\%).  Creatures are killed by
deallocating their memory, and removing them from both the reaper and
slicer queues.  Their ``dead'' code is not removed from the soup.

In the present system, the reaper uses a linear queue.  When a creature is
born it enters the bottom of the queue.  The reaper always kills the creature
at the top of the queue.  However, individuals may move up or down in the
reaper queue according to their success or failure at executing certain
instructions.  When a creature executes an instruction that generates an
error condition, it moves one position up the queue, as long as the
individual ahead of it in the queue has not accumulated a greater number
of errors.  Two of the instructions are somewhat difficult to execute
without generating an error, therefore successful execution of these
instructions moves the creature down the reaper queue one position, as long
as it has not accumulated more errors than the creature below it.

The effect of the reaper queue is to cause algorithms which are fundamentally
flawed to rise to the top of the queue and die.  Vigorous algorithms have a
greater longevity, but in general, the probability of death increases with age.

\LP
\bf 2.4.4 Mutation\rm
\eLP

In order for evolution to occur, there must be some change in the genome
of the creatures.  This may occur within the lifespan of an individual,
or there may be errors in passing along the genome to offspring.  In order
to insure that there is genetic change, the operating system randomly flips
bits in the soup, and the instructions of the Tierran language are
imperfectly executed.

Mutations occur in two circumstances.  At some background rate, bits are
randomly selected from the entire soup (e.g., 60,000 instructions totaling
300,000 bits) and flipped.  This is analogous to mutations caused by
cosmic rays, and has the effect of preventing any creature from being
immortal, as it will eventually mutate to death.  The background mutation
rate has generally been set at about one bit flipped for every 10,000
Tierran instructions executed by the system.

In addition, while copying instructions during the replication
of creatures, bits are randomly flipped at some rate in the copies.  The copy
mutation rate is the higher of the two, and results in replication errors.
The copy mutation rate has generally been set at about one bit flipped for
every 1,000 to 2,500 instructions moved.  In both classes of mutation,
the interval between mutations varies randomly within a certain range to
avoid possible periodic effects.

In addition to mutations, the execution of Tierran instructions is flawed
at a low rate.  For most of the 32 instructions, the result is off by plus
or minus one at some low frequency.  For example, the increment instruction
normally adds one to its register, but it sometimes adds two or zero.  The
bit flipping instruction normally flips the low order bit, but it sometimes
flips the next higher bit or no bit.  The shift left instruction normally
shifts all bits one bit to the left, but it sometimes shifts left by two
bits, or not at all.  In this way, the behavior of the Tierran instructions
is probabilistic, not fully deterministic.

It turns out that bit flipping mutations and flaws in instructions are not
necessary to generate genetic change and evolution, once the community
reaches a certain state of complexity.  Genetic parasites evolve which are
sloppy replicators, and have the effect of moving pieces of code around
between creatures, causing rather massive rearrangements of the genomes.
The mechanism of this ad hoc sexuality has not been worked out, but is
likely due to the parasites' inability to discriminate between live, dead
or embryonic code.

Mutations result in the appearance of new genotypes, which are watched
by an automated genebank manager.  In one implementation of the manager,
when new genotypes replicate twice, producing a genetically identical
offspring at least once, they are given a unique name and saved to disk.
Each genotype name contains two parts, a number and a three letter code.
The number represents the number of instructions in the genome.  The three
letter code is used as a base 26 numbering system for assigning a unique
label to each genotype in a size class.  The first genotype to appear in
a size class is assigned the label aaa, the second is assigned the label
aab, and so on.  Thus the ancestor is named 80aaa, and the first mutant
of size 80 is named 80aab.  The first creature of size 45 is named 45aaa.

The genebanker saves some additional information with each genome: the
genotype name of its immediate ancestor which makes possible the
reconstruction of the entire phylogeny; the time and date of origin;
``metabolic'' data including the number of instructions executed in the
first and second reproduction, the number of errors generated in the first
and second reproduction, and the number of instructions copied into the
daughter cell in the first and second reproductions (see Appendix C, D); some
environmental parameters at the time of origin including the search limit
for addressing, and the slicer power, both of which affect selection for size.

\LP
\bf 2.5 THE TIERRAN ANCESTOR\rm
\eLP

I have used the Tierran language to write a single self-replicating program
which is 80 instructions long.  This program is referred to as the
``ancestor'', or alternatively as genotype 0080aaa (Fig.\ 1).  The ancestor
is a minimal self-replicating algorithm which was originally written for use
during the debugging of the simulator.  No functionality was designed into
the ancestor beyond the ability to self-replicate, nor was any specific
evolutionary potential designed in.  The commented Tierran assembler and
machine code for this program is presented in Appendix C.

The ancestor examines itself to determine where in memory it begins and ends.
The ancestor's beginning is marked with the four no-operation template:
1 1 1 1, and its ending is marked with 1 1 1 0.  The ancestor locates its
beginning with the five instructions: ADRB, NOP\_0, NOP\_0, NOP\_0, NOP\_0.
This series of instructions causes the system to search backwards
from the ADRB instruction for a template complementary to the four NOP\_0
instructions, and to place the address of the complementary template
(the beginning) in the ax register of the CPU (see Appendix A).  A similar
method is used to locate the end.

Having determined the address of its beginning and its end, it subtracts
the two to calculate its size, and allocates a block of memory of this size
for a daughter cell.  It then calls the copy procedure which copies the entire
genome into the daughter cell memory, one instruction at a time.
The beginning of the copy procedure is marked by the four no-operation
template: 1 1 0 0.  Therefore the call to the copy procedure is accomplished
with the five instructions: CALL, NOP\_0, NOP\_0, NOP\_1, NOP\_1.

When the genome has been copied, it executes the DIVIDE instruction, which
causes the creature to lose write privileges on the daughter cell memory,
and gives an instruction pointer to the daughter cell (it also enters the
daughter cell into the slicer and reaper queues).  After this first
replication, the mother cell does not examine itself again; it proceeds
directly to the allocation of another daughter cell, then the copy procedure
is followed by cell division, in an endless loop.

Fourty-eight of the eighty instructions in the ancestor are no-operations.
Groups of four no-operation instructions are used as complementary templates
to mark twelve sites for internal addressing, so that the creature can locate
its beginning and end, call the copy procedure, and mark addresses for loops
and jumps in the code, etc.  The functions of these templates are commented
in the listing in Appendix C.

\pagebreak

\LP
\rule[6pt]{6.5in}{1pt}

\large \bf 3 RESULTS\rm \normalsize

\bf 3.1 EVOLUTION\rm
\eLP

Evolutionary runs of the simulator are begun by inoculating the soup of about
60,000 instructions with a single individual of the 80 instruction ancestral
genotype.  The passage of time in a run is measured in terms of how many
Tierran instructions have been executed by the simulator.  The original
ancestral cell executes 839 instructions in its first replication, and 813 for
each additional replication.  The initial cell and its replicating daughters
rapidly fill the soup memory to the threshold level of 80\% which starts the
reaper.  Typically, the system executes about 400,000 instructions in filling
up the soup with about 375 individuals of size 80 (and their gestating
daughter cells).  Once the reaper begins, the memory remains roughly 80\%
filled with creatures for the remainder of the run.

\LP
\bf 3.1.1 Micro-Evolution\rm
\eLP

If there were no mutations at the outset of the run, there would be no
evolution.  However, the bits flipped as a result of copy errors or background
mutations result in creatures whose list of 80 instructions (genotype) differs
from the ancestor, usually by a single bit difference in a single instruction.

Mutations in and of themselves, can not result in a change in the size of
a creature, they can only alter the instructions in its genome.  However,
by altering the genotype, mutations may affect the process whereby the
creature examines itself and calculates its size, potentially causing it
to produce an offspring that differs in size from itself.

Four out of the five possible mutations in a no-operation instruction convert
it into another kind of instruction, while one out of five converts it into
the complementary no-operation.  Therefore 80\% of mutations in templates
destroy or change the size of the template, while one in five alters the
template pattern.  An altered template may cause the creature to make
mistakes in self examination, procedure calls, or looping or jumps of the
instruction pointer, all of which use templates for addressing.

\LP
\bf 3.1.1.1 parasites\rm
\eLP

An example of the kind of error that can result from a mutation in a
template is a mutation of the low order bit of instruction 42 of the
ancestor (Appendix C).  Instruction 42 is a NOP\_0, the third component
of the copy procedure template.  A mutation in the low order bit would
convert it into NOP\_1, thus changing the template from 1 1 0 0 to: 1 1 1 0.
This would then be recognized as the template used to mark the end of the
creature, rather than the copy procedure.

A creature born with a mutation in the low order bit of instruction 42 would
calculate its size as 45.  It would allocate a daughter cell of size 45 and
copy only instructions 0 through 44 into the daughter cell.  The daughter
cell then, would not include the copy procedure.  This daughter genotype,
consisting of 45 instructions, is named 0045aaa.

Genotype 0045aaa (Fig.\ 1) is not able to self-replicate in isolated culture.
However, the semi-permeable membrane of memory allocation only protects write
privileges.  Creatures may match templates with code in the allocated memory
of other creatures, and may even execute that code.  Therefore, if creature
0045aaa is grown in mixed culture with 0080aaa, when it attempts to call the
copy procedure, it will not find the template within its own genome, but if
it is within the search limit (generally set at 200--400 instructions) of the
copy procedure of a creature of genotype 0080aaa, it will match templates, and
send its instruction pointer to the copy code of 0080aaa.  Thus a parasitic
relationship is established (see ECOLOGY below).  Typically, parasites begin
to emerge within the first few million instructions of elapsed time in a run.

\LP
\bf 3.1.1.2 immunity to parasites\rm
\eLP

At least some of the size 79 genotypes demonstrate some measure of
resistance to parasites.  If genotype 45aaa is introduced into a soup,
flanked on each side with one individual of genotype 0079aab, 0045aaa will
initially reproduce somewhat, but will be quickly eliminated from the soup.
When the same experiment is conducted with 0045aaa and the ancestor, they
enter a stable cycle in which both genotypes coexist indefinitely.  Freely
evolving systems have been observed to become dominated by size 79 genotypes
for long periods, during which parasitic genotypes repeatedly appear, but
fail to invade.

\LP
\bf 3.1.1.3 circumvention of immunity to parasites\rm
\eLP

Occasionally these evolving systems dominated by size 79 were successfully
invaded by parasites of size 51.  When the immune genotype 0079aab was tested
with 0051aao (a direct, one step, descendant of 0045aaa in which instruction
39 is replaced by an insertion of seven instructions of unknown origin), they
were found to enter a stable cycle.  Evidently 0051aao has evolved some way to
circumvent the immunity to parasites possessed by 0079aab.  The fourteen
genotypes 0051aaa through 0051aan were also tested with 0079aab, and none were
able to invade.

\LP
\bf 3.1.1.4 hyper-parasites\rm
\eLP

Hyper-parasite have been discovered, (e.g., 0080gai, which differs by 19
instructions from the ancestor, Fig.\ 1).  Their ability to subvert the energy
metabolism of parasites is based on two changes.  The copy procedure does not
return, but jumps back directly to the proper address of the reproduction loop.
In this way it effectively seizes the instruction pointer from the parasite.
However it is another change which delivers the coup de gr\^{a}ce: after
each reproduction, the hyper-parasite re-examines itself, resetting the bx
register with its location and the cx register with its size.  After the
instruction pointer of the parasite passes through this code, the CPU of the
parasite contains the location and size of the hyper-parasite and the
parasite thereafter replicates the hyper-parasite genome.

\LP
\bf 3.1.1.5 social hyper-parasites\rm
\eLP

Hyper-parasites drive the parasites to extinction.  This results in a
community with a relatively high level of genetic uniformity, and therefore
high genetic relationship between individuals in the community.  These are
the conditions that support the evolution of sociality, and social
hyper-parasites soon dominate the community.  Social hyper-parasites (Fig.\ 2)
appear in the 61 instruction size class.  For example, 0061acg is social in
the sense that it can only self-replicate when it occurs in aggregations.
When it jumps back to the code for self-examination, it jumps to a template
that occurs at the end rather than the beginning of its genome.  If the
creature is flanked by a similar genome, the jump will find the target
template in the tail of the neighbor, and execution will then pass into
the beginning of the active creature's genome.  The algorithm will fail unless
a similar genome occurs just before the active creature in memory.  Neighboring
creatures cooperate by catching and passing on jumps of the instruction
pointer.

It appears that the selection pressure for the evolution of sociality is that
it facilitates size reduction.  The social species are 24\% smaller than the
ancestor.  They have achieved this size reduction in part by shrinking their
templates from four instructions to three instructions.  This means that there
are only eight templates available to them, and catching each others jumps
allows them to deal with some of the consequences of this limitation as well
as to make dual use of some templates.

\LP
\bf 3.1.1.6 cheaters: hyper-hyper-parasites\rm
\eLP

The cooperative social system of hyper-parasites is subject to cheating,
and is eventually invaded by hyper-hyper-parasites (Fig.\ 2).  These cheaters
(e.g., 0027aab) position themselves between aggregating hyper-parasites so
that when the instruction pointer is passed between them, they capture it.

\LP
\bf 3.1.1.7 a novel self-examination\rm
\eLP

All creatures discussed thus far mark their beginning and end with templates.
They then locate the addresses of the two templates and determine their genome
size by subtracting them.  In one run, creatures evolved without a template
marking their end.  These creatures located the address of the template
marking their beginning, and then the address of a template in the middle of
their genome.  These two addresses were then subtracted to calculate half of
their size, and this value was multiplied by two (by shifting left) to
calculate their full size.

\LP
\bf 3.1.1.8 an intricate adaptation\rm
\eLP

The arms race described in the paragraphs above took place over a period of
a billion instructions executed by the system.  Another run was allowed to
continue for fifteen billion instructions, but was not examined in detail.
A creature present at the end of the run was examined and found to have
evolved an intricate adaptation.  The adaptation is an optimization technique
known as ``unrolling the loop''.

The central loop of the copy procedure performs the following operations:
1) copies an instruction from the mother to the daughter, 2) decrements the
cx register which initially contains the size of the parent genome, 3) tests
to see if cx is equal to zero, if so it exits the loop, if not it remains
in the loop, 4) increment the ax register which contains the address in the
daughter where the next instruction will be copied to, 5) increment the
bx register which contains the address in the mother where the next instruction
will be copied from, 6) jump back to the top of the loop.

The work of the loop is contained in steps 1, 2, 4 and 5.  Steps 3 and 6 are
overhead.  The efficiency of the loop can be increased by duplicating the
work steps within the loop, thereby saving on overhead.  The creature from
the end of the long run had repeated the work steps three times within the
loop, as illustrated in Appendix E, which compares the copy loop of the
ancestor with that of its decendant.

\LP
\bf 3.1.2 Macro-Evolution\rm
\eLP

When the simulator is run over long periods of time, hundreds of millions or
billions of instructions, various patterns emerge.  Under selection for small
sizes there is a proliferation of small parasites and a rather interesting
ecology (see below).  Selection for large creatures has usually lead to
continuous incrementally increasing sizes (but not to a trivial concatenation
of creatures end-to-end) until a plateau in the upper hundreds is reached.
In one run, selection for large size lead to apparently open ended size
increase, evolving genomes larger than 23,000 instructions in length.
These evolutionary patterns might be described as phyletic gradualism.

The most thoroughly studied case for long runs is where selection, as
determined by the slicer function, is size neutral.  The longest runs to date
(as much as 2.86 billion Tierran instructions) have been in a size neutral
environment, with a search limit of 10,000, which would allow large creatures
to evolve if there were some algorithmic advantage to be gained from larger
size.  These long runs illustrate a pattern which could be described as
periods of stasis punctuated by periods of rapid evolutionary change, which
appears to parallel the pattern of punctuated equilibrium described by
Eldredge \& Gould [15] and Gould \& Eldredge [19].

Initially these communities are dominated by creatures with genome sizes
in the eighties.  This represents a period of relative stasis, which has
lasted from 178 million to 1.44 billion instructions in the several long
runs conducted to date.  The systems then very abruptly (in a span of 1 or
2 million instructions) evolve into communities dominated by sizes ranging
from about 400 to about 800.  These communities have not yet been seen to
evolve into communities dominated by either smaller or substantially larger
size ranges.

The communities of creatures in the 400 to 800 size range also show a
long-term pattern of punctuated equilibrium.  These communities regularly come
to be dominated by one or two size classes, and remain in that condition for
long periods of time.  However, they inevitably break out of that stasis
and enter a period where no size class dominates.  These periods of rapid
evolutionary change may be very chaotic.  Close observations indicate that
at least at some of these times, no genotypes breed true.  Many
self-replicating genotypes will coexist in the soup at these times, but at
the most chaotic times, none will produce offspring which are even their same
size.  Eventually the system will settle down to another period of stasis
dominated by one or a few size classes which breed true.

\LP
\bf 3.2 DIVERSITY\rm
\eLP

Most observations on the diversity of Tierran creatures have been based on
the diversity of size classes.  Creatures of different sizes are clearly
genetically different, as their genomes are of different sizes.  Different
sized creatures would have some difficulty engaging in recombination if they
were sexual, thus it is likely that they would be different species.
In a run of 526 million instructions, 366 size classes were generated, 93
of which achieved abundances of five or more individuals.  In a run of
2.56 billion instructions, 1180 size classes were generated, 367 of which
achieved abundances of five or more.

Each size class consists of a number of distinct genotypes which also vary
over time.  There exists the potential for great genetic diversity within a
size class.  There are 32$^{80}$ distinct genotypes of size 80, but how many
of those are viable self-replicating creatures?  This question remains
unanswered, however some information has been gathered through the use
of the automated genebank manager.

In several days of running the genebanker, over 29,000 self-replicating
genotypes of over 300 size classes accumulated.  The size classes and
the number of unique genotypes banked for each size are listed in Table 1.
The genotypes saved to disk can be used to inoculate new soups individually,
or collections of these banked genotypes may be used to assemble ``ecological
communities''.  In ``ecological'' runs, the mutation rates can be set to zero
in order to inhibit evolution.

\LP
\bf 3.3 ECOLOGY\rm
\eLP

The only communities whose ecology has been explored in detail are those
that operate under selection for small sizes.  These communities generally
include a large number of parasites, which do not have functional copy
procedures, and which execute the copy procedures of other creatures within
the search limit.  In exploring ecological interactions, the mutation rate
is set at zero, which effectively throws the simulation into ecological time
by stopping evolution.  When parasites are present, it is also necessary
to stipulate that creatures must breed true, since parasites have a tendency
to scramble genomes, leading to evolution in the absence of mutation.

-- 
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Robert Chansky         uunet.uu.net!ucscc!sco.com!robertc, robertc@sco.com

From cellular-automata-request@Think.COM  Mon Sep  9 19:58:48 1991
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Date: 9 Sep 91 18:59:31
From: lord@churchy.gnu.ai.mit.edu (Tom Lord)
Organization: /home/gp2/lord/.organization
Subject: phase transitions in CA space
Message-Id: <LORD.91Sep9185931@churchy.gnu.ai.mit.edu>
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Sender: ca-request@Think.COM
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I have only the intro-to-chemistry notion of phase transitions.  Can
someone define the usage in this abstract for me?

>In studies of Cellular Automata (CA) it has been found that the most
>complex dynamics, including the capacity for universal computation, 
>is found in the vicinity of a phase transition in the space of CA
>rules. This phase transition exhibits many of the properties of 
>a second order --- or "critical" --- transition, suggesting a
>relationship between universal computation and critical dynamics.

t

From cellular-automata-request@Think.COM  Wed Sep 11 05:58:54 1991
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Date: 11 Sep 91 06:49:08 GMT
From: vangogh@ucscb.UCSC.EDU (vangogh)
Organization: University of California, Santa Cruz; Open Access Computing
Subject: Re: phase transitions in CA space
Message-Id: <20676@darkstar.ucsc.edu>
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In article <LORD.91Sep9185931@churchy.gnu.ai.mit.edu> lord@churchy.gnu.ai.mit.edu (Tom Lord) writes:
>I have only the intro-to-chemistry notion of phase transitions.  Can
>someone define the usage in this abstract for me?
>
>>In studies of Cellular Automata (CA) it has been found that the most
>>complex dynamics, including the capacity for universal computation, 
>>is found in the vicinity of a phase transition in the space of CA
>>rules. This phase transition exhibits many of the properties of 
>>a second order --- or "critical" --- transition, suggesting a
>>relationship between universal computation and critical dynamics.
>

While we're at it, what exactly is meant by the term "universal computation"?
Does this mean that the set of rules posted earlier [adding 00 to the string
if it begins with 0, adding 1101 to the end if it begins with 1] can somehow
perform all the functions of a finite state machine?  Am I greatly confusing
my definitions?

-- 

####  #       #   #    # #    # # #    #  ###   #  ##    #### # # ### ## # # ###
#   # #      # #  ##   # ##   # # ##   # #   #  # #      #    # # #   # # #   #
#   # #     #   # # #  # # #  # # # #  # #      #  ##    ##   # # ##  ##  #   #
####  #     ##### #  # # #  # # # #  # # # ###  #    #   #    # # #   # # #   #
#     #     #   # #   ## #   ## # #   ## #   #  #    #   #    # # #   # # #   #
#     ##### #   # #    # #    # # #    #  ###   #  ##    ####  #  ### # # #   #
Robert Chansky         uunet.uu.net!ucscc!sco.com!robertc, robertc@sco.com

From cellular-automata-request@Think.COM  Wed Sep 11 20:01:38 1991
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Date: Wed, 11 Sep 91 22:54:49 GMT
From: ies@nevanlinna.mit.edu (Irving E. Segal)
Organization: Dept. of Math., Wellesley College
Subject: Re: phase transitions in CA space
Message-Id: <1991Sep11.225449.16400@galois.mit.edu>
Newsgroups: comp.theory.cell-automata
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Sender: ca-request@Think.COM
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In article <20676@darkstar.ucsc.edu> vangogh@ucscb.UCSC.EDU (vangogh) writes:

>In article <LORD.91Sep9185931@churchy.gnu.ai.mit.edu> lord@churchy.gnu.ai.mit.edu (Tom Lord) writes:
>>I have only the intro-to-chemistry notion of phase transitions.  Can
>>someone define the usage in this abstract for me?

>>>In studies of Cellular Automata (CA) it has been found that the most
>>>complex dynamics, including the capacity for universal computation, 
>>>is found in the vicinity of a phase transition in the space of CA
>>>rules. This phase transition exhibits many of the properties of 
>>>a second order --- or "critical" --- transition, suggesting a
>>>relationship between universal computation and critical dynamics.

>While we're at it, what exactly is meant by the term "universal computation"?
>Does this mean that the set of rules posted earlier [adding 00 to the string
>if it begins with 0, adding 1101 to the end if it begins with 1] can somehow
>perform all the functions of a finite state machine?  Am I greatly confusing
>my definitions?

I'll give these a quick once-over.

1) Phase Transition.  This notion applies to any statistical mechanics system.
Here one assumes the system picks its state so as to maximize entropy subject
to whatever constraints one imposes (Gibb's law).  For example, for a gas
in a box one may impose the constraint that the energy equal  E , or that
the number of molecules equals  N.   One can then (if one has learned how) 
compute the expected values of various quantities (e.g. pressure)
in this "Gibbs state."  

Ifthe system is finite in size one practically always finds that these
expected values depend analytically on the constraint parameters 
(E, N , etc.).  One can then take the "infinite-volume limit," however.  
E.g., one can take V -> infty holding N/V, E/V constant.  
The expectation values of reasonable quantities, such as pressure, often cease
to be analytic in the limit, at certain values of the parameters... 
these are the phase transitions.   For example, if you plot pressure as a 
function of density and energy density for something like water you find
phase transitions corresponding to melting or boiling.

Much less technically, the phase transitions are where a system depending
on some parameter drastically changes character.  One can easily see these
in cellular automata; even though the CA on your computer is not really of 
infinite size if it's big enough you can barely tell the difference.  My pals 
at the CA lab at MIT (who never post here, but do *read* this newsgroup)
play with phase transitions analogous to the usual ones in physics 
all the time.   You can see magnets demagnetize as you heat them up, etc..

2)  Universal Computation.  One says some system does universal computation
if it can simulate any Turing machine.  This is a lot more than "performing
all the functions of *a* finite state machine" (my emphasis); it's
actually a lot more than performing all the functions of *any* finite
state machine.  Various cellular automata have been shown to be universal...
note that technically these must be infinite in size, but if they are big
enough they can simulate "lots" of Turing machines.  I don't know if
that simple rule you describe is universal.

3)  Now note that the phase transition spoken of in the abstract is
*not* quite the kind of phase transition I described (in the space of
parameters for some physical system), but a "phase transition" in a
more abstract "space of all CA rules".  Since the space of all CA rules
is not at all a vector space or manifold, the notion of analyticity
doesn't apply (at least not without making up some new definitions), so
I conclude that here "phase transition" is being used in the poetic sense
of "a point at which the character of something varies drastically."

I suspect it would be a lot of work to flesh the notions of the
abstract out to the point of getting a precise and true statement, and
I suspect nobody has yet done so.

jbaez@lucy.wellesley.edu




From cellular-automata-request@Think.COM  Thu Sep 12 06:00:38 1991
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Date: 11 Sep 91 10:48:15 GMT
From: skipper@diku.dk (Jakob Skipper)
Organization: Department of Computer Science, U of Copenhagen
Subject: Re: "Tierra"
Message-Id: <1991Sep11.104815.21384@odin.diku.dk>
Newsgroups: comp.theory.cell-automata
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jstravis@bass.bu.edu (John Travis) writes:

>In article <89243@bu.edu> jstravis@bu-pub.bu.edu (John Travis) writes:
>>the Danish researcher that modified ray's creature
>>to contain a "suicide" instruction recently found a bug that may nullify
>>some of his results. nevertheless, the concept of predators seems feasible 
>>enough that it could be included in tierra.
>>

And John Travis answered

>oops, sorry that wasn't in the NYTimes piece I guess. Ray's Tierra has a reaper
>program that keeps his memory block partly free so that his "organisms"
>gave room for copies of themselves. organisms that are "defective" or ld are
>removed by this reaper, but there are no actual predator organisms i.e.
>a program-organism doesn't kill others to free up space. a danish
>researcher removed the reaper--creating a population crunch--and added
>a suicide instruction into the "genome" or instruction set of some of
>his program-orgnaisms. These creatures didnot execute the suicide 
>instruction and kill themselves; instead parasites executing a host's
>code that included this suicide set unwittingly killed themselves--a 
>kind of predatory action one might claim. i'm not sure what the bug
>was but it seems a neat concept that should work.

Well, I am the mentioned Danish researcher. The above description
fits very well. The bug was in the statistics collection part of
the simulator. It gave wrong results, tricking me into believing
I had actually found predators in the system. I am still working
on this, it appears that even it these predators should be
possible, they are not that easy to evolve. The problem is, that
to evolve predators, you must remove the automatic killing of
other programs so that a program *must* kill another one to get
memory. But if you remove the automatic killing you will at the same
time slow down the evolution dramatically.

But the system is not just a hack of the Tierra system. It
contains other new things. The one-dimensional memory of
Tierra is replaced with a two-dimensional world, with memory
chopped into 16-byte pieces. Both code *and* data is addressed
by template, allowing sexual reproduction. The two-dimensional
world gives many new possibilities, such as flock formation.
And flock formation has been demonstrated (absolutely positively,
no bugs here) in the system.

Jakob Skipper
The Niels Bohr Institute/Institute of Datalogy
University of Copenhagen, Denmark

E-mail: skipper@diku.dk

From cellular-automata-request@Think.COM  Thu Sep 12 15:59:29 1991
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Date: 12 Sep 91 19:13:20 GMT
From: usenet@agate.berkeley.edu (USENET Administrator)
Organization: University of California, Berkeley
Subject: CA and self-organized criticality?
Message-Id: <1991Sep12.191320.17725@agate.berkeley.edu>
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Does anyone know of research on self-organized criticality [*] of cellular
automata, besides Bak, Chen, and Creutz's analysis of Life?

[* See January, 1991 Scientific American pp46-53]

Ken Shirriff				shirriff@sprite.Berkeley.EDU

From cellular-automata-request@Think.COM  Thu Sep 12 17:45:37 1991
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From: liw@ROCKVAX.ROCKEFELLER.EDU (Wentian Li)
Message-Id: <9109122145.AA03862@rocky7.rockefeller.edu>
To: cellular-automata@Think.COM
Subject: Re:self-organized criticality


>From: usenet@agate.berkeley.edu (USENET Administrator)
>Organization: University of California, Berkeley

>Does anyone know of research on self-organized criticality [*] of cellular
>automata, besides Bak, Chen, and Creutz's analysis of Life?
>[* See January, 1991 Scientific American pp46-53]
>Ken Shirriff                            shirriff@sprite.Berkeley.EDU


See, the paper by Bennett and Bourzutschky
"Is Game of Life critical?" in Nature 350, 468 (1991).
Their conclusion is that the Game of Life is *not*
critical, but subcritical, with a cutoff of the length
scale (the exact criticality means there willl be no 
such a cutoff). Bak, Chen, and Creutz didn't observe
the cutoff because their simulation was on a too small lattice.

There are also studies of the sand pile model *without*
dropping sand, and with periodic boundary conditions
(the sands are dumped back the system). Then it is 
a true cellular automaton (the original sand pile
model is *not* a true cellular automaton, because
one has to wait to check whether all dumping sand
processes are finished before adding a new grain of sand,
and this checking procedure is global, violating the
locality principle for cellular automata rules.) 
In this case, the system can either be subcritical, critical,
or supercritical by changing the averge height. So there
is a tuning parameter of the initial height.

I criticize the point of view that self-organized criticality
is "fundamentally different from the critical point at
phase transitions in equilibrium statistical mechanics
which can be reached only by tuning of a parameter" (Bak,
Tang, Wiesenfeld, "self-organized criticality: an
explanation of 1/f noise", Physical Review Letters, 59,
381--384 (1987)) in my paper "Phenomenology of non-local
cellular automata" (submitted to Journal of Statistical
Physics, 1991). 

In view of the space of all cellular automata rules, there
are subcritical rules (rules), supercritical rules (chaotic),
and "critical" ("complex" in a loose comparison) rules. 
Critical rules are sandwiched between subcritical and 
supercritical ones. There is *nothing* "fundamentally"
different from the critical point (here it's a critical 
hyper-surface because the dimension of the cellular automata
rule space is very large) in equilibrium statistical physics.
[Also see the paper: "Transition phenomena in cellular
automata rule space", Li, Packard, Langton, Physica D,
45, 77-94 (1990).]

The possible reason that these authors had a wrong conclusion
was perhaps because they tune some "irrelevant" parameters,
so that they always move around *on* the critical hyper-surface. 
But as long as the tuning parameters are "relevant", the criticality
will not be robust, and can disappear right away.


Wentian Li
Physics Department
Rockefeller University
1230 York Avenue
New York, NY 10021
liw@rockvax.rockefeller.edu


From cellular-automata-request@Think.COM  Fri Sep 13 19:00:48 1991
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Date: 12 Sep 91 15:33:07 GMT
From: skipper@diku.dk (Jakob Skipper)
Organization: Department of Computer Science, U of Copenhagen
Subject: Flock formation in Computer Zoo (Tierra-like system)
Message-Id: <1991Sep12.153307.21802@odin.diku.dk>
Newsgroups: comp.theory.cell-automata
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Upon request I will elaborate on the flock formation
found in the Computer Zoo (Tierra-like artificial life
simulator).

To summarize: we have a population of programs
reproducing and evolving due to mutations in this
simulator. All programs are placed in a
two-dimensional grid, on which they can move around.
Just like in Ray's Tierra system
there will (under certain conditions) appear small
parasite-like programa, that do not have themselves all
the code to reproduce. Instead they use the code of a
neighbour program to reproduce. Being this kind of
parasite is an advantage in that you will reproduce much
faster, but the cost is that you are dependent on other
programs in the neighbourhood to give you this code.

What happens is, that the system evolve a number of
different parasites. Alone, they miss a lot of code,
but when we take four different parasites and put them
together, they have enogh code to reproduce. And
since they can do that very fast (faster than a program
having to copy four times as much code), these small
parasite programs eradicate all other programs (a nice
example of symbiosis). But
since they are dependent on each other, they will 
cluster in one big flock on the grid. The dynamics of
this formation is quite simple: if a program is outside
of the initial flock, it will die. Therefore only
programs within the flock survive, and the flock
grows in size.

A program, that
for some reason moves outside the flock, has nobody
from whom it can borrow code, and it will die. As a
result, the programs do not just form a flock, they
also change their moving strategy to move in circles
instead of a straight line.

However, the flock is fragile. If for some the reason
the total number of programs in the flock fall below
some critical mass, the entire community collapses
very quickly, giving room for more robust programs
(so we also have punctuated equilibria).

There are also cases where a flock temporarily divides 
in two, but soon one of the flocks
collapses.

I hope this was a clear and understandable explanation.
If you want to know
more, a preliminary version of an article describing
this is avaiable from me electronically.

Kind regards

-- 
Jakob Skipper
The Niels Bohr Institute/Institute of Datalogy
University of Copenhagen, Denmark
E-mail:skipper@diku.dk

From cellular-automata-request@Think.COM  Mon Sep 16 19:01:21 1991
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Date: 16 Sep 91 21:40:49 GMT
From: steve@Pkg.Mcc.COM (Steve Madere)
Subject: Angular Momentum in Lattice Gas Automata
Message-Id: <1991Sep16.164049@Pkg.Mcc.COM>
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OK, folks here is a sticky physics question regarding
Lattice Gas Automata (Frisch, Hasslocher, & Pomeau).
(The simulation of fluid dynamics via particle 
dynamics on a discrete lattice space with discrete
velocities examples of physical situations that
would evoke different )

The lattice has finite sized spatial jumps between
nodes but we can make it appear continuous by looking
at a huge number of nodes.  By "rescaling" we make
translations continuous and thus recover translational
invariance.  Linear momentum consertation is saved!

For a hexagonal two dimensional lattice, there are
only six possible directions.  Therefore there is only
rotational symmetry for rotations that are exact multiples
of pi/3.   We cannot make this continuous by rescaling because
the group of rotations is compact (you've only got 2 pi, and
you just can't stretch it out anymore).  So we have no
continuous rotation operator to use for a generator of
angular momentum.

I must infer from this that these systems do not conserve
angular momentum and that angular momentum is not even a properly
defined quantity for them.  So, what does this do the dynamics
of the system and how would it cause it to differ from a real,
continuous fluid?  Any examples of physical situations that
would evoke different large scale behavior in a LGA than in 
a continuous fluid as a result of this angular momentum problem? 


Steve Madere
steve@pkg.mcc.com

From cellular-automata-request@Think.COM  Mon Sep 16 19:52:36 1991
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Subject: e-mail address change

For those of you on the list who correspond withy me directly, please use the
following address exclusively in the future (apologies to the rest of you):
stu@sunyit.edu.  Thanks.

From bmb@Think.COM  Mon Sep 16 23:03:32 1991
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In-Reply-To: Steve Madere's message of 16 Sep 91 21:40:49 GMT <1991Sep16.164049@Pkg.Mcc.COM>
Subject: Angular Momentum in Lattice Gas Automata


   Date: 16 Sep 91 21:40:49 GMT
   From: steve@Pkg.Mcc.COM (Steve Madere)

   OK, folks here is a sticky physics question regarding
   Lattice Gas Automata (Frisch, Hasslocher, & Pomeau).
   (The simulation of fluid dynamics via particle 
   dynamics on a discrete lattice space with discrete
   velocities examples of physical situations that
   would evoke different )

   The lattice has finite sized spatial jumps between
   nodes but we can make it appear continuous by looking
   at a huge number of nodes.  By "rescaling" we make
   translations continuous and thus recover translational
   invariance.  Linear momentum consertation is saved!

   For a hexagonal two dimensional lattice, there are
   only six possible directions.  Therefore there is only
   rotational symmetry for rotations that are exact multiples
   of pi/3.   We cannot make this continuous by rescaling because
   the group of rotations is compact (you've only got 2 pi, and
   you just can't stretch it out anymore).  So we have no
   continuous rotation operator to use for a generator of
   angular momentum.

   I must infer from this that these systems do not conserve
   angular momentum and that angular momentum is not even a properly
   defined quantity for them.

This is an interesting question.

The equation of motion of a lattice gas is

n_i(r + c_i,t + dt) = n_i(r,t) + C_i(n_*(r,t)),

where n_i(r,t) is 1 (0) if there is (not) a particle moving in direction
i at spatial position r at time t.  Then, dt is the time increment in
one generation, the index i runs over the lattice vectors c_i, and the
collision operator is denoted by C_i.  The notation C_i(n_*(r,t)) means
that C_i depends on n_j(r,t) for all possible values of j.

The microscopic particle velocity at (r,t) in direction i is then

c_i n_i(r,t).

The microscopic angular momentum due to the particle at (r,t) moving in
direction i is then

r x c_i n_i(r,t),

where x denotes the cross product.  The total angular momentum of the
fluid at time t is then

L(t) = Sum r x c_i n_i(r,t).
       r,i

Multiplying the equation of motion by c_i and crossing with r yields

Sum (r + c_i) x c_i n_i(r + c_i,t + dt) =
r,i

       = Sum r x c_i n_i(r,t) + Sum r x c_i C_i(n_*(r,t)),
         r,i                    r,i

where we have used the fact that c_i x c_i = 0.  Ignoring boundary
conditions, and juggling summation dummies, this becomes

L(t+dt) = L(t) + Sum r x [Sum c_i C_i(n_*(r,t))]
                  r        i

The sum in brackets vanishes by conservation of linear momentum, and we
get 

L(t+dt) = L(t),

so that angular momentum is indeed conserved.  The above argument is
constructed to be valid for any lattice gas with a localized collision
operator (i.e., it works for the 2D FHP lattice gas, the 3D FCHC lattice
gas, etc).

Another way to look at this is as follows: If we use a reference frame
in which the origin is pinned at the point of a collision, then the
incoming and outgoing angular momentum of the particles in a collision
is always zero, since the particles have zero impact parameter.

The original Phys. Rev. Lett. of FHP, and a subsequent J. Stat. Phys.
article by Wolfram show why macroscopic isotropy is obtained, even
though the microscopic dynamics are clearly anisotropic.  The question
of exactly how these discrete symmetries at the microscopic level become
Lie group symmetries at the macroscopic level is interesting, and
perhaps worth further thought.

   So, what does this do the dynamics
   of the system and how would it cause it to differ from a real,
   continuous fluid?  Any examples of physical situations that
   would evoke different large scale behavior in a LGA than in 
   a continuous fluid as a result of this angular momentum problem? 

If what you mean by a "real, physical fluid" is something that obeys the
Navier-Stokes equations, then lattice gases do not differ at all from
them, since they can be proven to obey them in the appropriate
hydrodynamic limit.

Best regards,
Bruce Boghosian

From cellular-automata-request@Think.COM  Tue Sep 17 10:59:18 1991
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From: liw@ROCKVAX.ROCKEFELLER.EDU (Wentian Li)
Message-Id: <9109171458.AA05004@rocky7.rockefeller.edu>
To: cellular-automata@Think.COM
Subject: preprint available


Thought someone might want a copy of the following
preprint (submitted to Journal of Statistical Physics,
also a working paper SFI-91-001)

Phenomenology of non-local cellular automata
Wentian Li, Santa Fe Institute

\begin{abstract}
The dynamical systems with non-local connections have potential
applications to economic and biological systems. This paper studies
the dynamics of non-local cellular automata. In particular, all two-state
three-input non-local cellular automata  are classified according to 
the dynamical behaviors starting from random initial configurations
and random wirings; though it is observed that sometimes a rule can
have different dynamical behaviors with different wirings.  The non-local
cellular automata rule space is studied using the mean-field
parameterization which is ideal for the situation of random wiring.
Non-local cellular automata can be considered as computers carrying
out computation at the level of each component. Their computational abilities
are studied from the point of view of whether they contain many
basic logical gates. Especially, I ask the question of whether
a three-input cellular automaton rule contains the three fundamental
logical gates:  two-input rules AND and OR, and one-input rule NOT. 
A particularly interesting ``edge of chaos" non-local cellular automaton,
the rule 184, is studied in detail. It is a system of coupled
``selectors" or ``multiplexers". It is also part of the Fredkin's gate
--- a proposed fundamental gate for conservative computations.  This
rule exhibits irregular fluctuations of the density, large coherent
structures, and long transient times.
\end{abstract}

The abstract is already too long, otherwise I can say more
about what I have done in this project. Send email to me at

wli@sfi.santafe.edu

Let me know whether you want LaTex file only (without figures
though) or you want a hard copy.

Wentian Li
Physics Department
Rockefeller University
1230 York Avenue
New York, NY 10021

From cellular-automata-request@Think.COM  Tue Sep 17 12:00:34 1991
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Date: 17 Sep 91 14:36:19 GMT
From: phillips@fozzie.nrl.navy.mil (Lee Phillips)
Organization: Naval Research Laboratory
Subject: Re: Angular Momentum in Lattice Gas Automata
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In article <1991Sep16.164049@Pkg.Mcc.COM> steve@Pkg.Mcc.COM (Steve Madere) writes:

   [....]
   I must infer from this that these systems do not conserve
   angular momentum and that angular momentum is not even a properly
   defined quantity for them.  So, what does this do the dynamics
   of the system and how would it cause it to differ from a real,
   continuous fluid?[....]

The dynamics of this system differ from a real fluid because, as far as I
know, there is no real fluid that obeys the strange equation of motion
that this discrete system solves.  The lattice gas, even after rescaling,
solves neither the Euler nor the Navier-Stokes equations, unless I have been
misinformed.  Note that conservation of angular momentum is relatively
unimportant here; for example, molecular dynamics (which really can solve
the N-S equations), or almost anything else, with periodic boundary
conditions, violates angular momentum, but the simulations are still
considered relevant.  With other types of boundaries, all conservation 
laws are obeyed.  
--
                                           Lee Phillips
                                           phillips@fozzie.nrl.navy.mil
                                           phillips@cmf.nrl.navy.mil
                                           phillips@lcp.nrl.navy.mil

From bmb@Think.COM  Tue Sep 17 14:07:26 1991
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Cc: ca@Think.COM, bmb@Think.COM
In-Reply-To: Lee Phillips's message of 17 Sep 91 14:36:19 GMT <DrPHILLIPS.91Sep17103619@fozzie.nrl.navy.mil>
Subject: Angular Momentum in Lattice Gas Automata


   Date: 17 Sep 91 14:36:19 GMT
   From: phillips@fozzie.nrl.navy.mil (Lee Phillips)

   In article <1991Sep16.164049@Pkg.Mcc.COM> steve@Pkg.Mcc.COM (Steve Madere) writes:

      [....]
      I must infer from this that these systems do not conserve
      angular momentum and that angular momentum is not even a properly
      defined quantity for them.  So, what does this do the dynamics
      of the system and how would it cause it to differ from a real,
      continuous fluid?[....]

   The dynamics of this system differ from a real fluid because, as far as I
   know, there is no real fluid that obeys the strange equation of motion
   that this discrete system solves.  The lattice gas, even after rescaling,
   solves neither the Euler nor the Navier-Stokes equations, unless I have been
   misinformed.  

Hello

You have been misinformed.  This is a rumor that lattice gas researchers
have been trying to contain for several years now.  It is not a
malicious rumor, as there are several possible plausible reasons for its
existence.  It is, nevertheless, misinformation.  So it is worth a
moment to examine the quirks of lattice gases that may have given rise
to this rumor, and to understand why they do not change the fact that
lattice gases can indeed be used to solve the incompressible
Navier-Stokes equations:

1) First let's look at the claims: Lattice gases for fluids, as put
forth by FHP and subsequent workers, are used to solve the
incompressible NS equations in 2D and 3D.  Other versions exist for
various diffusion equations, Burgers' equation, etc.  All these
equations are dissipative.  It has never been claimed by any lattice gas
researchers, to the best of my knowledge, that lattice gases are good
for solving the Euler equations, or any other Hamiltonian system.

2) Current lattice gas models work only for incompressible fluids.  The
equation of state of, for example, the FHP lattice gas is unphysical
(the pressure depends weakly on the hydrodynamic velocity).  In the
limit of incompressibility, however, the equation of state of a fluid is
irrelevant: It gets replaced by the condition that velocity is
divergenceless in any event.  No matter what equation of state a fluid
obeys, if the flow is kept at sufficiently low Mach number and the
fractional density variation is kept small (order Mach number squared),
then the fluid will satisfy the incompressible Navier-Stokes equations
(to order Mach number squared).

Unfortunately, there is nothing stopping people who don't know what they
are doing from simulating a lattice gas in a flow regime for which the
Mach number is quite high and the density variations are quite large.
They will get garbage.  They will then tell their friends that they got
garbage...

3) Because lattice gases lack Galilean invariance (the lattice itself is
a preferred reference frame), an extra factor appears in front of the
nonlinear convective term of the NS equations: Instead of

V . del V,

you get

g(rho) V . del V,

where V is hydrodynamic velocity, rho is density, and g is a known
function that emerges from the analysis.

Since we are working in the incompressible limit anyway, however, rho is
a constant number, and hence g(rho) is a constant number.  This being
the case, it is easy to rescale the velocity to get rid of this term.
That is, the velocity that you get by averaging the particles'
microscopic velocities will need to be multiplied by g(rho) to get the
real velocity of the simulation.  This, of course, is easy -- BUT YOU
HAVE TO DO IT!  The NS equations are nonlinear, so multiplying the
solution by a constant does *not* give you another solution.  Thus, if
you don't multiply the velocities that you measure by g(rho), then your
flow field will not satisfy the NS equations.  I actually know of a
study in which the researchers involved forgot to multiply by the g(rho)
factor, and went around announcing that lattice gases didn't measure up
to quantitative tests.

(NOTE: I should add that recent work in lattice gas modeling may give
researchers ways to get around the restrictions in (2) and (3) above, at
the expense of using somewhat more complicated rules.  That is, it may
be possible to construct lattice gas models with more physical equations
of state, and for which g(rho)=1.  This is nice, but I hope that it is
now clear that it is *not* essential for solving the incompressible NS
equations.)

4) Lattice gases have kinetic corrections -- that is, corrections due to
finite mean free path effects.  Molecular dynamics simulations have
these too -- as do *real* fluids.  As long as all scale lengths in the
problem are much greater than a mean free path, you get hydrodynamic
behavior and you obey the hydrodynamic equations.

Once again, unfortunately, there is nothing stopping people from running
simulations for flow around structures that have features with scales on
the order of a mean free path.  They get nonsense and they wonder why...

5) Finally, there are political reasons.  When it was first realized
that lattice gases could be used to simulate real hydrodynamics back in
1986, there was a great flurry of excitement.  During this time, a
number of rather excessive claims were made, such as the claim that we
now have the means to solve the turbulence problem, etc.  This did not
exactly "win friends and influence people" among researchers studying
other techniques of hydrodynamic simulation, etc.

In summary, lattice gases are like any other method in that they have
their advantages and disadvantages.  They are not a panacea, but they
are a good way of solving the incompressible NS equations in 2D or 3D in
many circumstances of interest.  They have, for example, given rise to
an exciting new way of simulating two-phase flow with interfacial
surface tension.  They have also given rise to lattice Boltzmann
methods, a new (ironically) floating-point method for hydrodynamics.
They have also greatly aided physicists in understanding the statistical
physics of fluids.

--Bruce Boghosian

From cellular-automata-request@Think.COM  Wed Sep 18 12:22:47 1991
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From: phillips@fozzie.nrl.navy.mil (Lee Phillips)
Message-Id: <9109181535.AA10907@fozzie.nrl.navy.mil>
To: bmb@Think.COM
Cc: ca@Think.COM, bmb@Think.COM
In-Reply-To: Bruce Boghosian's message of Tue, 17 Sep 91 14:07:24 EDT <9109171807.AA13575@aldebaran.think.com>
Subject: Angular Momentum in Lattice Gas Automata


   Current lattice gas models work only for incompressible fluids.  The
   equation of state of, for example, the FHP lattice gas is unphysical
   (the pressure depends weakly on the hydrodynamic velocity).  In the
   limit of incompressibility, however, the equation of state of a fluid is
   irrelevant: It gets replaced by the condition that velocity is
   divergenceless in any event.

This is the problem I was thinking of.  I have no problem with
rescaling to fix the convective term, or the rest of the points you
bring up.  A correct solution of the incompressible N-S equations will
yield a velocity field that is divergenceless everywhere for all time,
and a pressure field that satisfies the Laplace equation that you get
when you take the divergence of the N-S equation.  The lattice gas
methods fail both these tests; the velocity dependence of the pressure
leads to spurious sound waves.  A useful numerical method can be made
to approximate the correct solution to the governing equations more
accurately as its resolution, or some other parameter, is increased.
Can this be done with the lattice gas?  Are lattice gasses even 
marginally useful for Reynolds numbers over 100?  From what I have seen,
and I am only a spectator in this area, they give quantitatively
decent results only for creeping flow, which can be handled more
efficiently by other means.  I hope I am wrong, because the approach
is so interesting!

    They have also given rise to lattice Boltzmann
    methods, a new (ironically) floating-point method for hydrodynamics.

The (non-lattice) molecular dynamics solution of the Boltzmann equation,
with a monte-carlo method for the collision term, is proving to be a
good way to get fluid flows using parallel machines that can handle
many particles efficiently, and has none of the problems that the 
space lattice creates.  




From bmb@Think.COM  Wed Sep 18 17:33:48 1991
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In-Reply-To: Lee Phillips's message of Wed, 18 Sep 91 11:35:29 -0400 <9109181535.AA10907@fozzie.nrl.navy.mil>
Subject: Angular Momentum in Lattice Gas Automata


   Date: Wed, 18 Sep 91 11:35:29 -0400
   From: phillips@fozzie.nrl.navy.mil (Lee Phillips)

      Current lattice gas models work only for incompressible fluids.  The
      equation of state of, for example, the FHP lattice gas is unphysical
      (the pressure depends weakly on the hydrodynamic velocity).  In the
      limit of incompressibility, however, the equation of state of a fluid is
      irrelevant: It gets replaced by the condition that velocity is
      divergenceless in any event.

   This is the problem I was thinking of.  I have no problem with
   rescaling to fix the convective term, or the rest of the points you
   bring up.  A correct solution of the incompressible N-S equations will
   yield a velocity field that is divergenceless everywhere for all time,
   and a pressure field that satisfies the Laplace equation that you get
   when you take the divergence of the N-S equation.  The lattice gas
   methods fail both these tests; the velocity dependence of the pressure
   leads to spurious sound waves.  A useful numerical method can be made
   to approximate the correct solution to the governing equations more
   accurately as its resolution, or some other parameter, is increased.
   Can this be done with the lattice gas?  

Yes.  Let's adopt the notation:

n = density,
v = hydrodynamic velocity,
L = hydrodynamic length scale,
T = hydrodynamic time scale,
c = sound speed,
l = mean free path,
f = collision frequency,
q = viscosity.

Some relevant dimensionless quantities are then:

the Mach number M = v/c,
the Reynolds number R = L*v/q,
the Knudsen number K = l/L,
the Strouhal number S = f*T,
the fractional density variation across the domain N = (delta n)/n.

(Note that some of this notation is nonstandard; alas, there is no Greek
ascii.)

First note that dimensional analysis / kinetic theory tells us that

v ~ L/T,

f ~ c/l,

and

q ~ c*l.

From this, it follows that

S*R ~ 1/K^2.

Now, in order to have well-defined hydrodynamics (good scale separation
between the mean free path and the hydrodynamic length scale), we must
have K << 1.  There are two ways that this can happen:

R  ~ 1 and S >> 1  (Navier-Stokes limit)

and

R >> 1 and S  ~ 1  (Euler limit).

Lattice gases purport to operate in the first of these two asymptotic
regimes.  Treating R as order unity is necessary in order to wind up
with an equation that balances the two terms

partial v
---------   and   q * del^2 v,
partial T 

where del ~ 1/L.  It is easy to see that the ratio of the first term to
the second is ~R, and so R had better be order unity.  It follows that S
~ 1/K^2 >> 1.  (See Cercignani, "The Boltzmann Equation and its
Applications," Chapter V, for more discussion.)

Now that we have good kinetic/hydrodynamic scale separation, we turn our
attention to the issue of incompressiblity.  Incompressibility requires
that N ~ M^2 << 1.  (I will explain this more in a moment, but see
Landau and Lifschitz, "Fluid Mechanics," Chapter I, Section 10 for more
discussion.)  In most all theoretical treatments of lattice gases,
people additionally scale K (which must be small to ensure kinetic /
hydrodynamic separation) with M (which must be small to get
incompressibility); that is, they take K ~ M << 1, and they do both
perturbative analyses at once.  (They could be done successively, but
there is little point in doing so.)

To see why N ~ M^2 gives incompressibility, consider the compressible
equation for conservation of mass:

partial n
--------- + del . (n * v) = 0.
partial T

Expanding this gives

partial n
--------- + (v . del) n + n (del . v) = 0.
partial T

We now multiply by S/(f*n) to make this dimensionless with leading order
unity, and we order terms.  We see that

 S    partial n    S    delta n
--- * --------- ~ --- * ------- ~ N ~ M^2,
f*n   partial T   f*T      n

and

 S                   S    delta n
--- * (v . del) n ~ --- * ------- ~ N ~ M^2,
f*n                 f*T      n

while

 S                   S
--- * n (del . v) ~ --- ~ 1.
f*n                 f*T

Thus, the third term asymptotically dominates, and we are left with

del . v = 0 + O(v*M^2/L).

So the velocity is divergenceless to order M^2.

Next, consider the equation for conservation of momentum:

     partial v                           n*q
n * [--------- + (v . del)v] = -del [P - --- del . v] + n*q del^2 v,
     partial T                            3

where P is the pressure.  (Note: This is not the compressible equation
that you would end up with in a lattice gas analysis, but the terms that
differ are the same order as the terms that will be discarded by the
argument below -- so the argument below goes through.)  Multiply by
S/(M*n*c*f) this time, and order terms as before.  It is easy to see
that

   S          partial v    S    v/c
------- * n * --------- ~ --- * --- ~ 1,
M*n*c*f       partial T   f*T    M


   S                     S    v/c   T*v
------- n (v . del) v ~ --- * --- * --- ~ 1,
M*n*c*f                 f*T    M     L

and

   S                   S    v/c    q    T*v
------- n*q del^2 v ~ --- * --- * --- * --- ~ R ~ 1.
M*n*c*f               f*T    M    L*v    L

Next, remembering that del . v ~ O(v*M^2/L), we next have

   S                                 S     q    v/c   T*v
------- del [(n*q/3) * (del . v)] ~ --- * --- * --- * --- * M^2
M*n*c*f                             f*T   L*v    M     L

                                  ~ R*M^2 ~ M^2.

(Note that the terms that arise by applying the outside del operator to
n or q are smaller still -- q does depend on n for lattice gases, but
this shows that that's irrelevant too in this limit.)

Finally, we come to the term with the pressure.  This was the other
point that seemed bothersome.  The equation of state for the FHP gas is
something like

P = n*c^2 * (1 + v^2/c^2).

The second term in parenthesis is the bothersome one that depends on v.
Using the chain rule

        partial P           partial P
del P = --------- del n + ------------- del (v^2),
        partial n         partial (v^2)

            
      ~ c^2 del n + n del (v^2)


        n*c^2    del n   v^2
      ~ ----- * (----- + ---)
          L        n     c^2

Both terms in parenthesis contribute at the same order (O(M^2)).  It
follows that

   S               S      n*c^2          S    T*v    M
------- del P ~ ------- * ----- * M^2 ~ --- * --- * --- ~ 1.
M*n*c*f         M*n*c*f     L           f*T    L    v/c


So we finally get the pair of equations

del . v = 0 + O(v*M^2/L)


partial v                  del P
--------- + (v . del)v = - ----- + q del^2 v + O(v*M^2/T).
partial T                    n

which we recognize as the incompressible Navier-Stokes equations.  At
this point, P (regardless of what it may have depended on in the
compressible regime) and v constitute one scalar and one vector unknown,
and we have one scalar and one vector equation.  So we have a closed
system for P and v, and the equation of state is irrelevant.

You can get the elliptic equation for P that you mentioned in the usual
way: By taking the divergence of the above equation and solving for
del^2 P.  You find that it's the usual elliptic equation, once again to
within O(M^2).

I can understand why the original velocity dependence of P seems
bothersome, especially since the dP/dn and dP/dv terms contribute at the
same order, but the equation of state really does seem to be irrelevant
in the final result.  You are right, I think, that the sound waves are
messed up by this fact; but, once again, I think that the
*incompressible* features of the flow (sound waves, I would argue, are a
*compressible* feature) come out right as long as you're in the
asymptotic regime that I describe.  That is, I have given you all the
smallness parameters involved and told you how they scale so that the
result is exactly the incompressible NS equations in the limit.

Also, remember that lattice gas models have been developed without this
equation of state problem, though at the expense of more complicated
rules.  So if you're really dissatisfied with the above argument, you
can always retreat to one of those models.

From an implementational point of view, if you drive the flow at M = 0.1
and you measure N to be 0.01, and then you drop M to 0.9 and find that N
decreases to something like 0.81, then you can be pretty sure that N ~
M^2, and hence that you're in the asymptotic regime of
incompressibility.  (Of course, you also have to ensure that S ~ 1/K^2,
etc.)

I suspect that many lattice gas experimenters don't take adequate care
to ensure that they are in the correct asymptotic regime.  Lattice gases
are plagued by the fact that they are simultaneously very easy to
program and very prone to screwing up if executed in the wrong parameter
regime.

   Are lattice gasses even 
   marginally useful for Reynolds numbers over 100?  

Yes.  Current state of the art with them, I think, is something more
like order 500 to 1000.  I suspect that the group at LANL has done the
biggest simulations.  (Anybody there who is listening care to comment?)

   From what I have seen,
   and I am only a spectator in this area, they give quantitatively
   decent results only for creeping flow, which can be handled more
   efficiently by other means.  I hope I am wrong, because the approach
   is so interesting!

I think that they do better than that.  I vaguely recall studies in
which nonsteady phenomena were measured successfully (e.g., eddy
shedding rate past an obstacle as a function of Reynolds' number), but I
don't remember the details off the top of my head.  Look in the book
"Lattice Gas Methods for PDE's: Theory, Applications and Hardware" by
Doolen (North Holland, 1991) for a reading of papers, and especially a
nice list of references.  I agree, by the way, that experimental work
with these things has a long way to go before it approaches the level of
verification that other methods have had.  There is every reason,
however, to think that this will happen as the field matures.

Finally, I agree that if raw Reynolds' number performance is what you're
after, lattice gases are probably not the best thing to look at in many
cases.  They are good for lots of other flow situations, however: They
have given rise, as I mentioned before, to a wonderful new method for
simulating two-phase flow of immiscible fluids with a surface tension
interface.  (See references contained in the above book by Doolen for
details.)  Like any other method, lattice gases are good for some
problems and not good for some others; time will tell how they find
their niche.

       They have also given rise to lattice Boltzmann
       methods, a new (ironically) floating-point method for hydrodynamics.

   The (non-lattice) molecular dynamics solution of the Boltzmann equation,
   with a monte-carlo method for the collision term, is proving to be a
   good way to get fluid flows using parallel machines that can handle
   many particles efficiently, and has none of the problems that the 
   space lattice creates.  

Yes.  The Bird method and its variants are very nice.

Best regards,
Bruce

From cellular-automata-request@Think.COM  Thu Sep 19 19:18:35 1991
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Date: Thu, 19 Sep 91 19:09:46 EDT
From: Cameron.Esfahani@ub.cc.umich.edu
To: Cellular-Automata@ub.cc.umich.edu, cellular-automata@Think.COM
Message-Id: <9975175@ub.cc.umich.edu>
Subject: Removal from mailing list

Please remove me from the mailing list, I now have access to the group from
the Usenet and this just fills my mailbox with old messages.  I have sent 
this message before but nothing has happened, does anyone know why?
 
Cameron Esfahani

From hiebeler@Think.COM  Fri Sep 20 11:39:57 1991
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To: Cameron.Esfahani@ub.cc.umich.edu
Cc: Cellular-Automata@ub.cc.umich.edu, cellular-automata@Think.COM
In-Reply-To: Cameron.Esfahani@ub.cc.umich.edu's message of Thu, 19 Sep 91 19:09:46 EDT <9975175@ub.cc.umich.edu>
Subject: Removal from mailing list


Cameron,

  I do not see your name on the Cellular Automata mailing-list
distribution.  However, I do see the following address:
  CA-List@um.cc.umich.edu
on the list.

  I'd guess that you are on that Umich redistribution list.  You
should try to contact ca-list-request@um.cc.umich.edu, if that address
works.  If not, try postmaster@um.cc.umich.edu.

  Let me also remind everyone, please contact
cellular-automata-request@think.com for problems such as this (if you
leave out the "-request", everyone on the list sees the mail).

--
Dave Hiebeler                  | hiebeler@think.com
Thinking Machines Corporation  | (617) 234-4070

From cellular-automata-request@Think.COM  Fri Sep 20 13:25:39 1991
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Date: Fri, 20 Sep 91 13:24:19 -0400
From: phillips@fozzie.nrl.navy.mil (Lee Phillips)
Message-Id: <9109201724.AA15276@fozzie.nrl.navy.mil>
To: bmb@Think.COM
Cc: ca@Think.COM
Subject: Angular Momentum in Lattice Gas Automata
References: <9109182133.AA14752@aldebaran.think.com>

Some dimensional analysus leads you to conclude that 

   [....] in order to have well-defined hydrodynamics (good scale
   separation between the mean free path and the hydrodynamic length
   scale), we must have K << 1.  There are two ways that this can happen:

   R  ~ 1 and S >> 1  (Navier-Stokes limit)

   and

   R >> 1 and S  ~ 1  (Euler limit).

   Lattice gases purport to operate in the first of these two asymptotic
   regimes.  

However, the N-S equations are known experimentally to be good for Newtonian
liquids at least up to R ~ 10^4, and probably to 10^6.  The incompressible
N-S can also describe gasses at these elevated Reynolds numbers, as long as
M^2 << 1.  If when you claim that lattice gasses can solve the N-S
equations you mean that they are good for R ~ 1, that is one thing, but
later you say that the state of the art is R ~ 1000.  Also, if by 
"Euler limit" you mean that for R >> 1 the Euler equations can be 
substituted for the N-S equations, this is not correct.  The solutions
of one do not asymptotically approach the solutions of the other as
R is varied, because the order of the equations is different.

After attempting to explain the incompressible limit, you reach

   [....]the pair of equations

   del . v = 0 + O(v*M^2/L)


   partial v                  del P
   --------- + (v . del)v = - ----- + q del^2 v + O(v*M^2/T).
   partial T                    n

   which we recognize as the incompressible Navier-Stokes equations.

If this is the system of equations that the lattice gas generates a 
solution to, maybe this explains part of the problem.  You have used
"v" both as a characteristic velocity and as the velocity field
variable.  The velocity field varies by many orders of magnitude over
space and time.  It may be simultaneously true that M^2 << 1 and that
v*M^2/T ~ 1, for incompressible, Navier-Stokes flows.  This use 
of the O symbol is hard to understand.

I can't see that you have revealed any parameters that can be adjusted
in a lattice gas simulation to make the next run more accurate,
without varying the physical parameters of the system being simulated.
In, for example, a finite-difference solution of the N-S flow past a 
sphere at R = 1000, for example, if we want to increase accuracy
we can increase the resolution of the differencing grid (while decreasing
the timestep).  What is the analogy for the lattice gas?

   You are right, I think, that the sound waves are messed up [....]
   but, once again, I think that the *incompressible* features of
   the flow (sound waves, I would argue, are a *compressible* feature)
   come out right as long as you're in the asymptotic regime that I
   describe. 

I was too terse, and wound up being unclear.  What I meant by
"spurious sound waves" was not that the lattice gas calculates sound
waves incorrectly; I accept your information that it is only supposed
to be used for incompressible flows, and I agree that sound waves are
a compressible feature.  I meant that some people who have tried to
use this method to calculate an incompressible flow tell me that,
in what should be an imcompressible regime, that lattice gas generates
sound waves, and other spurious density gradients.  You mention that
people have tried to use the lattice gas outside the parameter range
of its validity, so maybe this is what happened.  But it seems as if 
this region of parameter space is so small that the lattice gas, or
at least the classical version we are discussing, can not be numbered
among the practical methods for numerically solving the incompressible
N-S equations.

   Also, remember that lattice gas models have been developed without this
   equation of state problem, though at the expense of more complicated
   rules.

Is there anything published yet on these new models?  

                                           Lee Phillips
                                           phillips@fozzie.nrl.navy.mil
                                           phillips@cmf.nrl.navy.mil

From bmb@Think.COM  Fri Sep 20 16:22:04 1991
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To: phillips@fozzie.nrl.navy.mil
Cc: ca@Think.COM, bmb@Think.COM
In-Reply-To: Lee Phillips's message of Fri, 20 Sep 91 13:24:19 -0400 <9109201724.AA15276@fozzie.nrl.navy.mil>
Subject: Angular Momentum in Lattice Gas Automata


   Date: Fri, 20 Sep 91 13:24:19 -0400
   From: phillips@fozzie.nrl.navy.mil (Lee Phillips)

   Some dimensional analysus leads you to conclude that 

      [....] in order to have well-defined hydrodynamics (good scale
      separation between the mean free path and the hydrodynamic length
      scale), we must have K << 1.  There are two ways that this can happen:

      R  ~ 1 and S >> 1  (Navier-Stokes limit)

      and

      R >> 1 and S  ~ 1  (Euler limit).

      Lattice gases purport to operate in the first of these two asymptotic
      regimes.  

   However, the N-S equations are known experimentally to be good for Newtonian
   liquids at least up to R ~ 10^4, and probably to 10^6.  The incompressible
   N-S can also describe gasses at these elevated Reynolds numbers, as long as
   M^2 << 1.  If when you claim that lattice gasses can solve the N-S
   equations you mean that they are good for R ~ 1, that is one thing, but
   later you say that the state of the art is R ~ 1000.  

Perhaps I should have been more clear.  You asked for a parameter for a
lattice gas simulation, such that in the limit as this parameter becomes
very small you get the NS equations exactly.  Let's call this parameter
epsilon.  What I told you was that if your simulation is such that

M ~ epsilon

N ~ epsilon^2

K ~ epsilon

S ~ 1/epsilon^2

R ~ 1,

then in the limit as epsilon goes to zero you will recover
incompressible NS exactly.  What I mean by saying that R ~ 1 (which I
alternately wrote as R ~ O(1)) is that it does not scale with epsilon --
not that it is a small number.  It can be 1000000 and still be O(1) in
this sense.  What I have given you is a scaling limit -- an asymptotic
ordering procedure for which you recover the incompressible NS equations
from the lattice gas equations of motion in the limit as a parameter
goes to zero.  (I thought that that's what you were asking for.)

The idea is that you come up with an ordering scheme in a certain
parameter, order every term in your dynamical equation in that
parameter, and retain only the terms that scale dominantly as the
parameter goes to its limit.  (For more on the type of asymptotic
analysis that I am using here, see the classic paper, "Asymptotology" by
Martin Kruskal, from "Mathematical Models in the Physical Sciences, ed.
S. Drobot, Prentice-Hall, Eaglewood Cliffs, NJ (1963).)

As you point out, it is only in the same sense that finite difference or
finite element methods simulate NS (grid spacing -> 0), so the fact that
lattice gases yield incompressible NS only in an asymptotic limit can
hardly be held against them.  Also, the proof that a non-lattice based
MD simulation obeys NS goes much the same way.

   Also, if by 
   "Euler limit" you mean that for R >> 1 the Euler equations can be 
   substituted for the N-S equations, this is not correct.  The solutions
   of one do not asymptotically approach the solutions of the other as
   R is varied, because the order of the equations is different.

I agree that the limit of large R to go from NS to Euler is very subtle
indeed.  All I'm saying here is that if you start from the microscopic
equations of motion and scale things as

K ~ epsilon

R ~ 1/epsilon^2

S ~ 1,

then the analysis known as the Hilbert expansion gives you the Euler
equations of motion.  If you instead scale things like

K ~ epsilon

R ~ 1

S ~ 1/epsilon^2,

then the analysis known as the Chapman-Enskog expansion gives you the
Navier-Stokes equations of motion.  Note that both of the above scalings
are consistent with the requirement that S*R*K^2 ~ 1.  They are simply
different asymptotic regimes.

   After attempting to explain the incompressible limit, you reach

      [....]the pair of equations

      del . v = 0 + O(v*M^2/L)


      partial v                  del P
      --------- + (v . del)v = - ----- + q del^2 v + O(v*M^2/T).
      partial T                    n

      which we recognize as the incompressible Navier-Stokes equations.

   If this is the system of equations that the lattice gas generates a 
   solution to, maybe this explains part of the problem.  You have used
   "v" both as a characteristic velocity and as the velocity field
   variable.  The velocity field varies by many orders of magnitude over
   space and time.  

Once again, I am interested only in a scaling limit.  It is true that v
may vary by a large amount over the domain.

   It may be simultaneously true that M^2 << 1 and that
   v*M^2/T ~ 1, for incompressible, Navier-Stokes flows.

No.  It only makes sense to specify the scaling of dimensionless
parameters.  That is why I multiplied all the equations by the
appropriate characteristic quantities necessary to make them
dimensionless before determining how the terms scaled.

   This use of the O symbol is hard to understand

It takes some getting used to, but it is, I think, standard usage.  (By
the way, Kruskal's explanation in the above-mentioned reference is much
better than mine.)

   I can't see that you have revealed any parameters that can be adjusted
   in a lattice gas simulation to make the next run more accurate,
   without varying the physical parameters of the system being simulated.
   In, for example, a finite-difference solution of the N-S flow past a 
   sphere at R = 1000, for example, if we want to increase accuracy
   we can increase the resolution of the differencing grid (while decreasing
   the timestep).  What is the analogy for the lattice gas?

Halve the Mach number (M -> M/2) (by halving whatever force you're using
to drive the flow), double the number of lattice sites along each
dimension of your domain (K -> K/2), and run for four times the number
of timesteps (S -> 4*S).  You will get the same Reynolds number (R ->
R), and you will (for M sufficiently small) find that the density
variation reduces fourfold (N -> N/4).  Your accuracy will improve.
Keep refining in this way, and you will converge to an *exact* solution
of the incompressible NS equations.

      You are right, I think, that the sound waves are messed up [....]
      but, once again, I think that the *incompressible* features of
      the flow (sound waves, I would argue, are a *compressible* feature)
      come out right as long as you're in the asymptotic regime that I
      describe. 

   I was too terse, and wound up being unclear.  What I meant by
   "spurious sound waves" was not that the lattice gas calculates sound
   waves incorrectly; I accept your information that it is only supposed
   to be used for incompressible flows, and I agree that sound waves are
   a compressible feature.  I meant that some people who have tried to
   use this method to calculate an incompressible flow tell me that,
   in what should be an imcompressible regime, that lattice gas generates
   sound waves, and other spurious density gradients.

This is interesting, as the above arguments indicate that the sound
waves should scale away in the asymptotic limit.  The M -> 0 limit is
like letting the sound speed go to infinity for fixed characteristic
hydrodynamic velocity.  When M gets sufficiently small, sound wave
phenomena should become vanishingly fleeting in its effects.  Do you
have a reference for the experiments in question.

   You mention that
   people have tried to use the lattice gas outside the parameter range
   of its validity, so maybe this is what happened.  But it seems as if 
   this region of parameter space is so small that the lattice gas, or
   at least the classical version we are discussing, can not be numbered
   among the practical methods for numerically solving the incompressible
   N-S equations.

This is indeed an issue.  MD simulations of hydrodynamics have the same
problem.  As I indicated in my last note, if raw Reynolds number
performance is all that you are after, you're probably better off using
other methods in many circumstances.

On the other hand, lattice gases begin to capture much physics that is
absent from other numerical hydrodynamic simulations, such as kinetic
fluctuations, etc.  You can set up a lattice gas simulation of the
Rayleigh-Taylor instability with an initially flat interface between the
heavier and lighter fluids, for example, and the interface will become
unstable without your having to give it any initial perturbation.
Microscopic fluctuations alone will precipitate the instability.  Some
researchers are interested in these sorts of hydrodynamic phenomena for
which the underlying kinetics "shines through."  For these sorts of
problems, lattice gases are like a poor mans' MD.  They give real
hydrodynamics based on an underlying kinetic model -- albeit a
ficticious kinetic model.  They may or may not ever be useful for
accurate hydrodynamic modelling -- time will tell -- but they have
already been undeniably useful for people studying the statistical
mechanics of fluids.

The bottom line is that if you want to simulate hydrodynamics based on
any kind of kinetics (lattice gas, molecular dynamics, or Monte Carlo),
it is not easy.  As supercomputers improve, however, it will become
easier.

      Also, remember that lattice gas models have been developed without this
      equation of state problem, though at the expense of more complicated
      rules.

   Is there anything published yet on these new models?  

Umm...  check out "A Gailiean-Invariant Immiscible Lattice Gas" by
Gunstensen and Rothman (Physica D 47 (1991) 53-63).  You might also want
to check out other articles in this special issue, as well as the
references.  There may be other references that address this issue more
directly (Gunstensen and Rothman are more worried about Galilean
invariance than the equation of state -- though the issues are related).
If there are any lattice gas researchers listening who know of better
references to the realistic equation-of-state lattice gases, please help
out here.

Regards,
Bruce

From cellular-automata-request@Think.COM  Sat Sep 21 05:03:51 1991
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Date: 21 Sep 91 00:44:15 GMT
From: minar@reed.edu (Nelson Minar)
Organization: Reed College, Portland, OR
Subject: A-Life II book is out
Message-Id: <m0kNvS6-0000W1C@vishnu.reed.edu>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM

I heard some people say they had a hard time getting a copy of
"Artificial Life II", the proceedings of the Feb 1990 workshop. I just
bought a copy yesterday at the Portland State University bookstore
(there is an alife class this year) for $34.10. It looks great.
--
                __ 
minar@reed.edu  \/                                        Love under will.

From cellular-automata-request@Think.COM  Mon Sep 23 15:02:56 1991
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Date: 23 Sep 91 18:23:29 GMT
From: rdb@scs.carleton.ca (Robert D. Black)
Organization: School of Computer Science, Carleton University, Ottawa, Canada
Subject: Industrial Use of Cellular Automata
Message-Id: <1991Sep23.182329.21471@cunews.carleton.ca>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM

A general interest question:

Are cellular automata being used in industrial applications yet,
or are they still only being used in research?  It would seem that
this would be a growth industry in the next ten years or so...

--
--
Robert Black                               rdb@scs.carleton.ca
School of Computer Science
Carleton University, Ottawa, Canada

From cellular-automata-request@Think.COM  Tue Sep 24 04:02:22 1991
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Date: 24 Sep 91 05:11:33 GMT
From: mburke@yoda.eecs.wsu.edu (Matthew Burke - grad student)
Organization: Washington State University
Subject: CA software for the Iris
Message-Id: <1991Sep24.051133.20495@serval.net.wsu.edu>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM



Basically the Subj: says it all.  Are there any software packages
for the Silicon Graphics Iris workstation?

PD would be preferable.

Thanks,

Matt
-- 
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%      Matthew M. Burke        mburke@yoda.eecs.wsu.edu    %
%   Where am I and what am I doing in this handbasket?     %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

From cellular-automata-request@Think.COM  Wed Sep 25 08:01:21 1991
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Date: 25 Sep 91 10:59:19 GMT
From: martel@marvin.mr.sintef.no (Paulo Martel)
Organization: University of Trondheim, Norway
Subject: Reposting of Tierra articles
Message-Id: <martel.685796359@marvin>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
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Hello

Can somebody send me a copy of the "Tierra" articles that appeared earlier
in this group ?

Thanks in advance,

Paulo
--
Paulo Martel             |  e-mail: martel@marvin.mr.sintef.no
MR-Center                |  phone: +47-7-997700
SINTEF		         |  FAX:   +47-7-997708
N-7034 Trondheim, NORWAY |

From cellular-automata-request@Think.COM  Thu Sep 26 06:01:30 1991
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Date: 26 Sep 91 07:55:16 GMT
From: clong@remus.rutgers.edu (Chris Long)
Organization: Rutgers Univ., New Brunswick, N.J.
Subject: The BL_1 Cellular Automata
Message-Id: <Sep.26.03.55.14.1991.22599@remus.rutgers.edu>
Newsgroups: comp.theory.cell-automata,alt.fractals
Sender: ca-request@Think.COM
To: ca@Think.COM


The following one-dimensional cellular automata generates very
beautiful and highly complex pictures, somewhat reminiscent of looking
at Pascal's triangle modulo a fixed integer (and very fractal-like).
Each time slice should be represented as one line on the display.
Simple, but very pretty.  After this gets too mundane try BL_2,
which is the 2-d analogue.

I have a very fast MSDOS program which handles up to SVGA for BL_1
(but only for the card I have, which is probably fairly common) if
anyone is interested; the source code is in Turbo Pascal.


BL_1 (Balsley-Long)

Initial conditions:

N = Maximum number of rows - 1

{ Two immortal, immutable organisms live on the edge }

{ 1,1 and 1,3 work well for Color_0,Color_N }

  L[0] := Color_0
  L[N] := Color_N

Algorithm:

{ Initialize all organisms as dead, except for the immortals }

For i:=2 to N-1 do
  L[i] := 0;

n:=0;

While (whatever) do
begin

  For i:=2 to N-1 do
  begin

    { Organisms take on the sum of the colors of their two neighbors }

    M[i] := L[i-1] + L[i+1];

    { If organism takes in too much color it dies; ~150 works great for
      Over_Eat if you can display 256 colors}

    If (M[i]>Over_Eat) then M[i]:=0;

  end;

  Swap(L,M);

  { The coordinates are ~(i,n), color is ~L[i] for drawing }

  Draw(L,n);

  n:=n+1;

end;
-- 
Chris Long, 272 Hamilton St. Apt. 1, New Brunswick NJ  08901  (908) 846-5569

"In a study of schoolboys, an educator discovered a correlation between size
 of feet and quality of handwriting.  The boys with the larger feet were,
 on the average, older."        Wallis & Roberts, _The Nature of Statistics_

From cellular-automata-request@Think.COM  Thu Sep 26 14:15:24 1991
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Date: Thu, 26 Sep 1991 13:38-0400
From: Allan C. Wechsler <ACW@YUKON.SCRC.Symbolics.COM>
Subject: Universality
To: stu@sunyit.edu, cellular-automata@Think.COM
In-Reply-To: <9109162340.AA04257@sct60a.sunyct.edu>
Message-Id: <19910926173831.4.ACW@PALLANDO.SCRC.Symbolics.COM>

[Thanks for the new address -- I tried to get this through to you a
while ago but was unable to.]

    Date: Tue, 30 Jul 1991 21:00 EDT
    From: stu@sct60a.sunyct.edu (Stu Card)

    I hate to show my ignorance so blatantly, but could you point me to a
    CONCISE reference which will explain:

    1) the meaning (formal) of universality;

    2) the stopping problem / Turing test;

    3) a concrete example of a UTM with a small number of states and symbols?

    Thanks.

Gosharoony, nothing CONCISE, I think.  Let me get on the soapbox and
give it a try.  What I'll do is give short definitions in terms of
concepts only slightly more primitive.  If you aren't familiar with
THOSE concepts, ping me again and I'll elaborate.  That way I won't make
the mistake of telling you something you don't know.

Let TM be the class of all Turing machines.  A class C of automata is
universal if every automaton in TM can be modeled by one in C.

A UTM is not really a Turing machine.  It is just the controller of one
without a specific input.  So really it is a class of automata, that
differ only in the initial contents of the tape.  For this class to be
universal, there has to be a way to encode any TM onto just the tape of
the UTM.

A concrete example went out to CA recently.

The stopping problem (usually called the Halting Problem, after its
inventor, Arnold Problem) is that there is no effective procedure for
determining whether a given automaton from a universal class will ever
halt.  The Halting Problem is a good spoiler to rebut people who claim
that a given class of automata is universal.  If you can prove they all
halt, or even give an algorithm for telling whether they halt, then the
class can't possibly be universal.

The Turing Test is an concept in the philosophy of AI; it is a thought
experiment designed as a criterion of intelligence.  It is not related
to the Halting Problem -- at least, not transparently related.

From cellular-automata-request@Think.COM  Thu Sep 26 17:02:10 1991
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Date: 26 Sep 91 19:45:22 GMT
From: ies@banach.mit.edu (Irving E. Segal)
Organization: MIT, Department of Mathematics
Subject: Re: Universality
Message-Id: <1991Sep26.194522.14369@galois.mit.edu>
Newsgroups: comp.theory.cell-automata
References: <9109162340.AA04257@sct60a.sunyct.edu>, <19910926173831.4.ACW@PALLANDO.SCRC.Symbolics.COM>
Sender: ca-request@Think.COM
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In article <19910926173831.4.ACW@PALLANDO.SCRC.Symbolics.COM> ACW@YUKON.SCRC.Symbolics.COM (Allan C. Wechsler) writes:
>[Thanks for the new address -- I tried to get this through to you a
>while ago but was unable to.]
>
>    Date: Tue, 30 Jul 1991 21:00 EDT
>    From: stu@sct60a.sunyct.edu (Stu Card)
>
>    I hate to show my ignorance so blatantly, but could you point me to a
>    CONCISE reference which will explain:
>
>    1) the meaning (formal) of universality;
>
>    2) the stopping [halting] problem / Turing test;
>
>    3) a concrete example of a UTM with a small number of states and symbols?
>
>    Thanks.

There are plenty of references for this sort of thing but... except
for the Turing test, which is rather unrelated to all of the rest... a good
place to start would be "Computability and Logic," by Boolos and Jeffrey.

John Baez

From cellular-automata-request@Think.COM  Mon Sep 30 13:23:09 1991
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From: autodesk!air!rudy@fernwood.mpk.ca.us (Rudy Rucker)
Message-Id: <9109301647.AA02336@air.acad>
To: ca@Think.COM
Subject: Universality


Two good informal discussions of Turing universality are Douglas
Hofstadter's Godel Escher BAch, and Rudy Rucker's Mind Tools.

From cellular-automata-request@Think.COM  Tue Oct  1 20:17:15 1991
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Date: 1 Oct 91 19:23:24 GMT
From: butterwo@arras.cs.unc.edu (Jeff Butterworth)
Subject: Interesting LGA Model
Message-Id: <6505@borg.cs.unc.edu>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
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I recently read a LGA (lattice gas automata) paper that explains an
interesting way of achieving isotropy in 2D.  This method modifies a
rectangular lattice (like HHP) rather than using a triangular one (like FHP).

The paper is "Lattice Gas Models for 3D Hydrodynamics" by D'Humeires,
Lallemand, and Frisch in Europhysics Letters, 2(4), pp. 291-297 (1986).

The basic change is that diagonal connections are made between each site
and it's second nearest neighbors.  Particles moving along these diagonal
paths must still get to the next site in one time step, so they move at
sqrt(2) times the speed of the vertical and horizontal particles.
One might ask how these faster particles can collide with slower particles
and still conserve mass and momentum.  To do this, stationary particles
are also introduced.  An example collision involving all three speeds
is shown below.

Here we see a a speed 1 particle approaching a site from the left.
A speed sqrt(2) particle is approaching the same site from the upper right.
After the collision, one particle moves down and the other stops.
Mass and momentum are conserved.

p == particle
* == site

before		movement	collision
		phase		phase
	  
 *  *  *         *  *  *          *  *  *
      p 
	              
 *p *  *         *  *p *          *  p  *
	           p                 p   
	  
 *  *  *         *  *  *          *  *  *

The "graphics" above show nine sites of a lattice.  Each particle is shown
next to the lattice site at which it is stored.  The direction of movement
of a particle is determined by drawing a vector from the site to the particle.

The fact that this lattice is rectangular makes the implementation simpler
than FHP for some computers.  Does anyone have an opinion about whether
this method will work better, as well, or worse than FHP?  Does anyone think
that this method still doesn't give isotropy?  Unfortunately, I don't
know anything about group theory so I'm not qualified to answer these
questions.


Jeff Butterworth

Home: 100-H Misty Woods Circle, Chapel Hill, NC 27514 (919) 967-7359
School: 342 Sitterson, UNC-Chapel Hill, NC 27599 (919) 962-1849
E-Mail:	butterwo@cs.unc.edu

"Note that this could cause a memory fault if the old area was tiny,
 and the moon is gibbous."
			- Comment in the source code for BSD 4.3 realloc()

From cellular-automata-request@Think.COM  Wed Oct  2 06:15:00 1991
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Date: 1 Oct 91 13:35:17 GMT
From: isgtec!bmw@bloom-beacon.MIT.EDU (Bruce M. Walker)
Organization: ISG Technologies Inc., Mississauga Ontario
Subject: Re: Industrial Use of Cellular Automata
Message-Id: <1546@isgtec.UUCP>
Newsgroups: comp.theory.cell-automata
References: <1991Sep23.182329.21471@cunews.carleton.ca>
Sender: ca-request@Think.COM
To: ca@Think.COM

In article <1991Sep23.182329.21471@cunews.carleton.ca> rdb@scs.carleton.ca (Robert D. Black) writes:
> Are cellular automata being used in industrial applications yet,
> or are they still only being used in research?  It would seem that
> this would be a growth industry in the next ten years or so...

Well, I don't know if this fits your criteria exactly, but ... I built
a CA from the August 1988 Scientific American "Computer Recreations"
article about the hodgepodge machine.  I did this to prove out my new
implementation of a parallel threads scheduler for my companies'
parallel processing engine.  My Hodgepodge computes and displays a
1024x1024 array of 8 bit colour pixels and displays the generation
updates in near real time.  This program turned out to be a terrific
system test and was used that way for two years after by the the
hardware designers and manufacturing. If there were any memory faults
or timing problems, the characteristic Hodgepodge patterns would
immediately change in dramatic ways.  An experienced trouble-shooter
could pinpoint a problem area just by the specific shift in the pattern
from the "norm".

Hodgepodge, for those who don't know, mimics the wave-actions present
in certain chemical reactions including the Belousov-Zhabotinsky
reaction.  The hodgepodge algorithm was cooked-up by Gerhardt and
Schuster of the University of Bielefeld in West Germany.

Each pixel must undergo one of three transformations from one
generation to the next, from healthy to infected, infected to ill, or
ill back to healthy:

    a cell is "healthy" (pixel value 0), "infected" (0<n<255) or "ill" (255).
    A represents the number of infected cells in its neighborhood.
    B represents the number of ill cells in its neighborhood.
    S is the number of state neighbors of a cell (typically 4 or 8)
    k1, k2 are adjustable weighting parameters
    g is the rate of infection (also an adjustable parameter)

The state of a healthy cell at time t+1 is

    [A/k1]+[B/k2]

The state of an infected cell at time t+1 is

    [S/A]+g	--but is truncated to be no greater than "ill".

An ill cell becomes healthy again at t+1.

Using a von Neumann neighborhood (four orthoganally adjacent cells), my
hodgpodge updates the 1024x1024 display at around 8-10 Hz running on 16
TMS320C25 DSP's with shared data memory.  With an appropriate spectrum
selected for the colour map, the resulting animated display can be
quite beautiful and hypnotic.

--
   "CAUTION: OBJECTS IN SCREEN ARE CLOSER THAN THEY APPEAR"
bmw@isgtec.uucp  [ ..uunet!utai!lsuc!isgtec!bmw ]  Bruce Walker

From hiebeler@Think.COM  Wed Oct  2 07:29:03 1991
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From: David Hiebeler <hiebeler@Think.COM>
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To: isgtec!bmw@bloom-beacon.MIT.EDU
Cc: ca@Think.COM
In-Reply-To: Bruce M. Walker's message of 1 Oct 91 13:35:17 GMT <1546@isgtec.UUCP>
Subject: Industrial Use of Cellular Automata


  To use cellular automata as a system test, I'd think one would
prefer a much more "fragile" rule than the Hodgepodge rule.  I haven't
played with Hodgepodge very much, but I'm surprised that if you have a
single-bit error somewhere in the array, it makes a noticable visual
difference.

  On the other hand, if you were to run something like the
"End-of-world" rule (second-order reversible billiard-ball rule)
described in _Cellular Automata Machines_ by Toffoli and Margolus,
with a contrived initial condition containing some particles and
mirrors, then if you get a single bit error somewhere, you're very
likely to get a visual explosion originating from that point in the
array.

  For those unfamiliar with the rule, it uses a 2-bit Moore
neighborhood (9 neighbors, counting the center cell).  It uses the 2
bits to record the present and past states of the cell.  If you have
some particles bouncing around, you are actually using very few of the
possible states of the system (you are ignoring all those arrays that
have a past state that could not correspond to the present state under
the desired particle-motion rule).  If you get a single-bit error,
suddenly you leave the small cycle of states you were on, and the
system will start exploring the set of these "nonsense" states.
Basically, it looks like an explosion of "random" cells taking over
the array.

  Also, you'd want to run such a test on a cell-array that practically
fills memory, and locate your lookup-table in different areas in
memory for different runs.  A single-bit mutation in the lookup table
(rather than the cell array) may quite likely produce *no* effect at
all; I believe very little of the lookup-table is actually used, when
running on such carefully constructed arrays (as opposed to running on
a completely random array, which wouldn't be very useful).


--
Dave Hiebeler                  | Internet: hiebeler@think.com
Thinking Machines Corporation  | UUCP: {uunet,harvard}!think!hiebeler
245 First Street               | Bitnet: hiebeler%think.com@mitvma.bitnet
Cambridge, MA 02142  USA       | Phone:  (617) 234-4070

From cellular-automata-request@Think.COM  Wed Oct  2 12:16:38 1991
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Date: 2 Oct 91 15:15:16 GMT
From: rick@xing.unocal.com (Richard Ottolini)
Organization: Unocal Corporation, Anaheim, California
Subject: Re: Industrial Use of Cellular Automata
Message-Id: <1991Oct2.151516.3906@unocal.com>
Newsgroups: comp.theory.cell-automata
References: <1991Sep23.182329.21471@cunews.carleton.ca>, <1546@isgtec.UUCP>
Sender: ca-request@Think.COM
To: ca@Think.COM

>In article <1991Sep23.182329.21471@cunews.carleton.ca> rdb@scs.carleton.ca (Robert D. Black) writes:
>> Are cellular automata being used in industrial applications yet,
>> or are they still only being used in research?  It would seem that
>> this would be a growth industry in the next ten years or so...

The criteria are:
(1) Are cellular automata a more efficient way of calculating than current methods?
(2) Are CA a more accurate way than currently?
(3) Do they permit the computation/prediction of new phenenoma unable by current
methods?

The verdict is not in yet on geological applications.
One big interest is the modeling of seismic waves in complicated geology.  Perhaps
CA might be more efficient.
Another interest is the modeling of fluid flow in complex subsurface geometries.
Complex geometries are simpler to specify in CA systems, so this is an advantage.
Yet another interest is relation between CA and the fractal distributions of
phenomena in nature.  It is recognized that some CA systems such as nucleated
diffision and reaction diffusion give rise to fractal distributions.  This may
help to explain fracture distributions in petroleum reservoirs and the behavior
of earthquake faults.

From cellular-automata-request@Think.COM  Wed Oct  2 12:23:01 1991
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Date: Wed, 2 Oct 91 10:22:34 MDT
From: cgl@t13.Lanl.GOV (Chris Langton)
Message-Id: <9110021622.AA11831@t13.lanl.gov>
To: ca@Think.COM
Subject: Re: phase transitions in CA space


   I should have gotten to this sooner, but I have been buried in projects
and plagued by sick computers.....

  In a previous article, "jbaez@lucy.wellesley.edu" writes:
  
>  In article <20676@darkstar.ucsc.edu> vangogh@ucscb.UCSC.EDU 
>  (vangogh) writes:

>>In article <LORD.91Sep9185931@churchy.gnu.ai.mit.edu> 
>>lord@churchy.gnu.ai.mit.edu (Tom Lord) writes:
>>>I have only the intro-to-chemistry notion of phase transitions.  Can
>>>someone define the usage in this abstract for me?

>>>>In studies of Cellular Automata (CA) it has been found that the most
>>>>complex dynamics, including the capacity for universal computation, 
>>>>is found in the vicinity of a phase transition in the space of CA
>>>>rules. This phase transition exhibits many of the properties of 
>>>>a second order --- or "critical" --- transition, suggesting a
>>>>relationship between universal computation and critical dynamics.		

    ( several ">" levels deleted )
    
>I'll give these a quick once-over.

   ( jbaez goes on to define phase transitions, universal computation,
      and etc.....ending with:
      
>3)  Now note that the phase transition spoken of in the abstract is
>*not* quite the kind of phase transition I described (in the space of
>parameters for some physical system), but a "phase transition" in a
>more abstract "space of all CA rules".  Since the space of all CA rules
>is not at all a vector space or manifold, the notion of analyticity
>doesn't apply (at least not without making up some new definitions), so
>I conclude that here "phase transition" is being used in the poetic sense
>of "a point at which the character of something varies drastically."

>I suspect it would be a lot of work to flesh the notions of the
>abstract out to the point of getting a precise and true statement, and
>I suspect nobody has yet done so.

>jbaez@lucwwwwy.wellesley.edu


  As the abstract refered to above concerns my work, I'll fill in 
some of the details. An abstract, of course, can be little more
that a teaser to attract people's attention to the following article or
talk. They are of little use when separated from the article or talk
that contains the substantiating details. 

  The term "phase-transition" is intended to be taken seriously, and 
is not being used merely in a "poetic" sense. One can define parameters 
over the space of CA rules, vary these parameters, and observe that 
statistical measures of the CA dynamics behave as if the system was 
undergoing a phase-transition. E.g., transient times diverge, correlation 
lengths diverge, and so forth. Furthermore, the phase transitions are, 
in fact, observed in a "space of parameters".

  Here's a first-order approximation to the story. For further information,
check out my paper "Computation at the Edge of Chaos" in Physica D V42,
pp. 12-37 (1990), and/or my PhD Thesis of the same name, available from
University Microfilms. 

  (Related work has been (or is being) done by Stuart Kauffman 
(U. Penn & Santa Fe Institute) on random boolean netowrks; Jim 
Crutchfield (Berkeley) for continuous dynamical systems, including 
coupled lattice maps; Wentian Li and Norman Packard (Santa Fe Institute
and Center for Complex Systems Research) for cellular automata
and other dynamical systems; G. Vichniac, P. Tamayo, and H. Hartman 
(various institutions) for inhomogeneous and probabilistic cellular 
automata; and Howard Guttowitz (Center for Nonlinear Studies and Complex 
Systems Group, LANL) for cellular automata); Brosl Hasslacher at 
LANL is working on an analytic proof (details at 10....;-).

Here's the story:

  Wolfram proposed the following four qualitative classes of behavior 
for cellular automata:

    Class I:   relaxes to homogeneous fixed-point.
    
    Class II:  relaxes to heterogeneous fixed point   
               or short period behavior. 
               
    Class III: relaxes to chaotic, random behavior
               with little apparent global structure.
               
    Class IV:  exhibits complex, local dynamics, which may 
               eventually collapse to periodic behavior
               after a long transient period.
               (The game of LIFE is included in this class).

Wolfram hypothesized that CA in the last class might be capable
of supporting universal computation (it is known that LIFE does),
and that it is this capacity which is responsible for the 
complexity of their behavior.

Although there have been several attempts to come up with 
quantitative measures which cleanly distinguish between these
classes, they have met with somewhat limited success.  Classification
alone is not enough, what is needed is an understanding of the way 
in which proposed classes are related to one another.

What I have found for CA's is that there are a number of parameters 
that one can define over the space of possible CA rules, and that 
as one varies these parameters, one passes through the above 
classes in the following order:

    I -> II -> IV -> III
    
That is, the complex rules are located *between* the periodic rules 
and the chaotic rules. Furthermore, approaching and passing through 
the complex rules has very much the flavor of approaching and 
passing through a physical phase-transition: transients
increase, correlation lengths grow, diffusion begins to look 
``anomolous,'' and statistics fail to converge. In some cases, 
there is a sudden jump from periodic to chaotic behavior, suggesting
a first-order phase-transition. On other occasions, however, there 
seems to be a smoother transition, with transients diverging effectively
to infinity, suggesting a second-order or ``critical'' transition.

These ``critical'' rules exhibit all of the characteristics of the 
class IV rules mentioned above, especially the long-transients, which
suggest the well-known second-order phenomenon of ``critical 
slowing down.'' They also exhibit many of the qualitative properties
of the game of LIFE, supporting things like gliders, blinkers and other 
such structures, whose interactions are quite complicated.
These structures can be employed in the construction of AND, OR,
and NOT gates, and so forth, as is done in the proof that the game of 
LIFE is universal.

  Now, given the evidence that class IV rules might support universal 
computation generically, and noting that class IV rules are found in
the vicinity of what looks --- both qualitatively and quantitatively 
--- like a second-order phase-transition between ordered and disordered
CA behaviors, the following conjecture suggests itself: 

     There is a fundamental connection between phase-transitions 
     and computation - especially between second-order phase-
     transitions and universal computation. 
   
  This implies that information processing is likely to become an 
important factor in the dynamics of a physical system in the vicinity 
of a phase-transition between ordered and disordered behavior. 
Thus, computation may emerge spontaneously in physical
systems at the edge of chaos.

  Once one observes this apparent relationship, one expects to find 
many associations between the phenomenology of computation and the 
phenomenology of phase-transitions. And one finds them. First of all, 
one can identify an analog of the various computational complexity 
classes in the manner in which the transient times of a CA are related 
to the size of the CA. These transient times are effectively independent 
of the size of the array far from the transition regime, they begin 
to be able to ``feel'' array size closer to the transition regime, 
and can come to exhibit exponential dependence on array size in the 
vicinity of the second-order transition. Furthermore, this dependency 
reverses itself as one progresses beyond the transition. As one proceeds 
into the chaotic regime, the randomness of the self-generated noise in 
the system increases to the point where the size of the array cannot be 
felt by the local dynamics, and the transients are again short and 
independent of array size.  

  Second, there is also an analog of Turing's Halting problem. In the 
vicinity of the transition, the transients become extremely long, and 
in an unbounded system could become infinite: it may take an arbitrarily 
long time before a CA in the transition regime ultimately reaches a periodic 
dynamics. One may be able to identify the periodic regime with computations 
which always halt, the chaotic regime with computations which NEVER halt, 
and the transition regime with computations which may or may not halt, 
depending on uncomputable details of the initial state and the rule.

  Thus, it may be that we have been playing around with critical phenomena 
for a long time, only we have been calling them ``computations.'' We 
should consider computers to be physical systems which are designed to be 
at, or very near, their critical point, and the computations which run on 
them the behavior of a critical system when its initial state has been very 
carefully arranged.

  The halting problem for computers can then be viewed as a special case 
of a physical system becoming ``critically slowed down'' to the point 
where it becomes impossible to predict its ultimate state, suggesting 
that the occurance of critical slowing down in nature is evidence that 
physical systems must sometimes effectively solve an intractable problem 
in order to relax a steady state. 

  This phenomenon can also be observed in the optimazation technique of 
simulated annealing. Note that simulated annealing schedules typically 
call for the longest times to be spent in the vicinity of the phase 
transition. One explanation for this is that the system is dealing 
with the phenomenon of critical-slowing-down, in which the dynamics 
of the annealed system itself can be viewed as actively computing 
the way towards a solution via an emergent computation.

  There are many more details, including quantitative measurements, in
the papers mentioned above. 

   Hope this helps...

   Chris Langton

   Complex Systems Group
   MS B213, Theoretical Division	Phone: (505) 667-9471
   Los Alamos National Laboratory	Email: cgl@t13.lanl.gov
   Los Alamos, New Mexico, USA		FAX:   (505) 665-3003
   87545




From cellular-automata-request@Think.COM  Wed Oct  2 17:15:22 1991
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Date: 2 Oct 91 20:34:36 GMT
From: shirriff@allspice.Berkeley.EDU (Ken Shirriff)
Organization: University of California, Berkeley
Subject: Reaction-diffusion patterns?
Message-Id: <1991Oct2.203436.7737@agate.berkeley.edu>
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I'm looking for information:
The October Scientific American (p121) mentions Andrew Witkin at CMU is
generating interesting natural patterns and textures by using
reaction-diffusion models.  Does anyone know if he's published anything
recently on this? (My library search was unsuccessful.)

Ken Shirriff		shirriff@sprite.Berkeley.EDU

From cellular-automata-request@Think.COM  Wed Oct  2 17:17:35 1991
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Date: Wed, 2 Oct 91 19:42:17 GMT
From: jbaez@lagrange.mit.edu (John C. Baez)
Organization: MIT, Department of Mathematics
Subject: Re: phase transitions in CA space
Message-Id: <1991Oct2.194217.5858@galois.mit.edu>
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In article <9110021622.AA11831@t13.lanl.gov> cgl@t13.Lanl.GOV (Chris Langton) writes:
>>3)  Now note that the phase transition spoken of in the abstract is
>>*not* quite the kind of phase transition I described (in the space of
>>parameters for some physical system), but a "phase transition" in a
>>more abstract "space of all CA rules".  Since the space of all CA rules
>>is not at all a vector space or manifold, the notion of analyticity
>>doesn't apply (at least not without making up some new definitions), so
>>I conclude that here "phase transition" is being used in the poetic sense
>>of "a point at which the character of something varies drastically."

>  The term "phase-transition" is intended to be taken seriously, and 
>is not being used merely in a "poetic" sense. One can define parameters 
>over the space of CA rules, vary these parameters, and observe that 
>statistical measures of the CA dynamics behave as if the system was 
>undergoing a phase-transition. E.g., transient times diverge, correlation 
>lengths diverge, and so forth. Furthermore, the phase transitions are, 
>in fact, observed in a "space of parameters".

.... and many more details.

I haven't had time to absorb all the details, which look interesting, 
but the reason why I thought your use of the term "phase transition"
was poetic... or let's say, an extension of the usual use!... seems
not to be answered.  Namely, in a typical cellular automaton, where
the state of each cell is given by a *finite* amount of information
(rather than continuous variables), the space of cellular automaton
rules (at least those with a certain neighborhood) is a *finite set*,
so one can't continuously vary the cellular automaton rule, and one
can't define rates at which correlation lengths diverge, etc..  

In other words, unless the space of cellular automaton rules is
a manifold (which it's not), you must mean something different when
you talk about phase transitions, which are usually points on a
manifold at which certain functions (thermodynamic quantities) are
non-analytic.

To put it yet another way: in your posing you talk about a 
cellular automaton rule being "between" other rules.  How do
you define a rule to be "between" two other rules?

jbaez@lucy.wellesley.edu



From cellular-automata-request@Think.COM  Wed Oct  2 18:16:37 1991
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Date: 2 Oct 91 21:26:38 GMT
From: rick@xing.unocal.com (Richard Ottolini)
Organization: Unocal Corporation, Anaheim, California
Subject: Re: Reaction-diffusion patterns?
Message-Id: <1991Oct2.212638.9143@unocal.com>
Newsgroups: comp.theory.cell-automata,sci.bio
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Sender: ca-request@Think.COM
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In article <1991Oct2.203436.7737@agate.berkeley.edu> shirriff@sprite.berkeley.edu (Ken Shirriff) writes:
>I'm looking for information:
>The October Scientific American (p121) mentions Andrew Witkin at CMU is
>generating interesting natural patterns and textures by using
>reaction-diffusion models.  Does anyone know if he's published anything
>recently on this? (My library search was unsuccessful.)

Yes, there are two articles in the 1991 SIGGRAPH Proceedings (Computer Graphics,
vol 25, no. 4) on reaction-diffusion.
(Too recent for library databases.)

From cellular-automata-request@Think.COM  Thu Oct  3 10:15:44 1991
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Date: 3 Oct 91 13:18:28 GMT
From: marek@msel.unh.edu (Marek W Lugowski)
Organization: UNH Marine Systems Engineering Laboratory
Subject: Re: phase transitions in CA space
Message-Id: <1991Oct3.131828.2759@nic.unh.edu>
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jbaez@lagrange.mit.edu (John C. Baez), responding to Chris Langton writes:

>I haven't had time to absorb all the details, which look interesting, 
>but the reason why I thought your use of the term "phase transition"
>was poetic... or let's say, an extension of the usual use!... seems
>not to be answered....
...
>To put it yet another way: in your posing you talk about a 
>cellular automaton rule being "between" other rules.  How do
>you define a rule to be "between" two other rules?

It seems to me there is no conflict here.  One can determine the
cardinality of CA rules by indexing them with the parameterization of
CA space Chris is talking about.  In fact, finiteness of cellular
information has nothing to do with ordering.  In computer science it
is often possible to order the states of an automaton without the
automaton being a manifold or displaying analytic properties.

In sum, there is no reason for phase transition phenomena not to
possess discrete granularity.  In fact, the real thermodynamical
systems being modeled by analytical means such as partial differential
equations are themselves wholly discrete.

				-- Marek

Marek Lugowski
Marine Systems Engineering Laboratory
Marine Program Building
University of New Hampshire
Durham, NH 03824

marek@msel.unh.edu
-- 
			chicks with bricks come.
			chicks with blocks come.
			chicks with bricks and
			blocks and clocks come.      -- Dr. Seuss

From cellular-automata-request@Think.COM  Thu Oct  3 11:59:31 1991
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Date: Thu, 3 Oct 1991 12:02-0400
From: Allan C. Wechsler <ACW@YUKON.SCRC.Symbolics.COM>
Subject: Re: phase transitions in CA space
To: marek@msel.unh.edu, ca@Think.COM
In-Reply-To: <1991Oct3.131828.2759@nic.unh.edu>
Message-Id: <19911003160205.0.ACW@PALLANDO.SCRC.Symbolics.COM>

    Date: Thu, 3 Oct 1991 09:18 EDT
    From: marek@msel.unh.edu (Marek W Lugowski)

    In sum, there is no reason for phase transition phenomena not to
    possess discrete granularity.  In fact, the real thermodynamical
    systems being modeled by analytical means such as partial differential
    equations are themselves wholly discrete.

				    -- Marek

Even so, let's suppose that the phase transition is diagnosed by some
(non-impressionistic) measurement.  Let's say (for example) that this
measurement changes sign at the phase transition.  Then a rule which
yielded a measurement of zero would be "critical", and if we believe
Langton's thesis, we would expect universality for that rule.

My difficulty is, that since the space of rules is discrete, and the
diagnostic measurement is surely statistical, it will never be exactly
zero.  Each actual rule will lie on one side or other of the frontier.
You might have to run the rule for a long time to determine which side
of the line it was on, but it would always be on one side or the other.

On the other hand, universality is a well-defined, provable property
that some rules have and some rules don't.  There's clearly a "universal
region" in rule space.  Langton's thesis, identifying universal automata
with critical points on a phase-boundary, can't be right in its exact
form.  And if the thesis is weakened, to say that universal rules lie
"near" a transition, then we are left wondering just how near is near.

			    chicks with bricks come.
			    chicks with blocks come.
			    chicks with bricks and
			    blocks and clocks come.      -- Dr. Seuss
                                                         (1904-1991)
                                                         (*snif*) :-(

From hiebeler@Think.COM  Thu Oct  3 12:28:17 1991
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To: jbaez@lagrange.mit.edu
Cc: ca@Think.COM
In-Reply-To: John C. Baez's message of Wed, 2 Oct 91 19:42:17 GMT <1991Oct2.194217.5858@galois.mit.edu>
Subject: phase transitions in CA space


  One other thing to consider, is that Langton and others have also
done some work extending the results toward the case of a CA with an
infinitely large rule table, which lets you take an infinitesimal step
through parameter space.  Actually, that's not quite true, since they
were using a statistical method to "fake" an infinite rule-table, so
you still lose something, but what you gain (I believe) is that your
transition becomes much sharper, rather than scattered out over the
parameter space.

  That is discussed, I think, in a paper by Langton and Wooters, also
in the Physica D V42.  Someone please correct me if I'm wrong about
that.

--
Dave Hiebeler                  | hiebeler@think.com
Thinking Machines Corporation  | (617) 234-4070

From cellular-automata-request@Think.COM  Thu Oct  3 23:59:49 1991
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Date: Thu, 3 Oct 91 23:59:35 EDT
From: liw@ROCKVAX.ROCKEFELLER.EDU (Wentian Li)
Message-Id: <9110040359.AA14522@rocky7.rockefeller.edu>
To: cellular-automata@Think.COM
Subject: Re: phase transition and univ computation


There is a comment I would like to make. The cellular
automaton Game of Life being both a complex rule
and a universal computer doesn't mean that every
cellular automaton that can carry out universal
computation exhibits complex dynamics with a *typical*
initial condition.

The crucial point is that for a CA being a universal
computer implies we can design some *special* initial
condition to do arbitrarily complicated calculation,
but for a CA being a complex rule implies that it
shows complicated dynamics with some *random* initial
conditions. Note that the lattice size can go to
infinity, so *arbitrarily* complicated computation
for those universal CAs can be carried out by some
*arbitrarily* complicated initial condition, which
typically will not be sampled when we choose the 
initial condition randomly.

I found out that the connection between complex
dynamics and universal computers is particularly
weak for non-local cellular automata. For a non-local
CA, as long as its rule table contains, for example,
AND and NOT logical gates (OR can be constructed from
AND and NOT, by the way), one can construct any logical
functions, so it is then a universal computer. There
are plenty of non-local CAs satisfy the requirement,
but *very few* of them exhibit complex, non-trivial
dynamics!


Wentian Li
Physics Department
Rockefeller University
1230 York Avenue
New York, NY 10021


From cellular-automata-request@Think.COM  Fri Oct  4 08:15:43 1991
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Date: 4 Oct 91 11:08:41 GMT
From: heitkoet@gorbi.informatik.uni-dortmund.de (Joerg Heitkoetter)
Organization: University of Dortmund, Germany
Subject: Re: Industrial Use of Cellular Automata
Message-Id: <3861@laura.UUCP>
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In article <1546@isgtec.UUCP>, bmw@isgtec.uucp (Bruce M. Walker) writes:
|> Well, I don't know if this fits your criteria exactly, but ... I built
|> a CA from the August 1988 Scientific American "Computer Recreations"
|> article about the hodgepodge machine.  I did this to prove out my new
|> implementation of a parallel threads scheduler for my companies'
|> parallel processing engine.  My Hodgepodge computes and displays a
|> 1024x1024 array of 8 bit colour pixels and displays the generation
|> updates in near real time.  This program turned out to be a terrific
|> system test and was used that way for two years after by the the
|> hardware designers and manufacturing. If there were any memory faults
|> or timing problems, the characteristic Hodgepodge patterns would
|> immediately change in dramatic ways.  An experienced trouble-shooter
|> could pinpoint a problem area just by the specific shift in the pattern
|> from the "norm".
A very interesting idea.

|> Hodgepodge, for those who don't know, mimics the wave-actions present
|> in certain chemical reactions including the Belousov-Zhabotinsky
|> reaction.  The hodgepodge algorithm was cooked-up by Gerhardt and
|> Schuster of the University of Bielefeld in West Germany.
Well. It wasn't invented to mimic the BZ reaction at all, this phaenomenom
"fell from the stars", when Martin was on his PhD Thesis.
I worked with Heike (Schuster) and Martin (Gerhardt), when Heike joined our
the group for Biomathematics at the Max-Planck-Institute for
Ernaehrungsphysiology,
for a short time.

|> Each pixel must undergo one of three transformations from one
|> generation to the next, from healthy to infected, infected to ill, or
|> ill back to healthy:
|> 
|>     a cell is "healthy" (pixel value 0), "infected" (0<n<255) or "ill"
|> (255).
|>     A represents the number of infected cells in its neighborhood.
|>     B represents the number of ill cells in its neighborhood.
|>     S is the number of state neighbors of a cell (typically 4 or 8)
|>     k1, k2 are adjustable weighting parameters
|>     g is the rate of infection (also an adjustable parameter)
|> 
|> The state of a healthy cell at time t+1 is
|> 
|>     [A/k1]+[B/k2]
|> 
|> The state of an infected cell at time t+1 is
|> 
|>     [S/A]+g	--but is truncated to be no greater than "ill".
|> 
|> An ill cell becomes healthy again at t+1.
|> 
|> Using a von Neumann neighborhood (four orthoganally adjacent cells), my
|> hodgpodge updates the 1024x1024 display at around 8-10 Hz running on 16
|> TMS320C25 DSP's with shared data memory.  With an appropriate spectrum
|> selected for the colour map, the resulting animated display can be
|> quite beautiful and hypnotic.
|> 
|> --
|>    "CAUTION: OBJECTS IN SCREEN ARE CLOSER THAN THEY APPEAR"
|> bmw@isgtec.uucp  [ ..uunet!utai!lsuc!isgtec!bmw ]  Bruce Walker
If someone wants Martin's *original* program, called "infekt2.c", written
on an ATARI ST using it's GEM capabilities, with a minor update by
myself to compile it using Borland's Turbo-C, please let me know...

So long

	
	-joke

--
Joerg Heitkoetter
Systems Analysis Group
University of Dortmund, Germany
(heitkoet@gorbi.informatik.uni-dortmund.de).

From bmb@Think.COM  Fri Oct  4 16:34:59 1991
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To: liw@ROCKVAX.ROCKEFELLER.EDU
Cc: cellular-automata@Think.COM, bmb@Think.COM
In-Reply-To: Wentian Li's message of Thu, 3 Oct 91 23:59:35 EDT <9110040359.AA14522@rocky7.rockefeller.edu>
Subject: phase transition and univ computation


   Date: Thu, 3 Oct 91 23:59:35 EDT
   From: liw@ROCKVAX.ROCKEFELLER.EDU (Wentian Li)

   There is a comment I would like to make. The cellular
   automaton Game of Life being both a complex rule
   and a universal computer doesn't mean that every
   cellular automaton that can carry out universal
   computation exhibits complex dynamics with a *typical*
   initial condition.

   The crucial point is that for a CA being a universal
   computer implies we can design some *special* initial
   condition to do arbitrarily complicated calculation,
   but for a CA being a complex rule implies that it
   shows complicated dynamics with some *random* initial
   conditions. Note that the lattice size can go to
   infinity, so *arbitrarily* complicated computation
   for those universal CAs can be carried out by some
   *arbitrarily* complicated initial condition, which
   typically will not be sampled when we choose the 
   initial condition randomly.

   I found out that the connection between complex
   dynamics and universal computers is particularly
   weak for non-local cellular automata. For a non-local
   CA, as long as its rule table contains, for example,
   AND and NOT logical gates (OR can be constructed from
   AND and NOT, by the way), one can construct any logical
   functions, so it is then a universal computer. There
   are plenty of non-local CAs satisfy the requirement,
   but *very few* of them exhibit complex, non-trivial
   dynamics!

There's something that I don't understand about this.

If a particular CA can support a universal computer, then, with certain
initial conditions, it can support a computer that is programmed to,
say, clear out a vicinity, or perhaps somehow orgainize all the cells in
that vicinity into nice neat rows of stable objects.  It might be a
computer that organizes a given region in this way, and then moves on,
trying to organize other regions similarly -- kind of a "combine" of
sorts.

Now I agree that for any finite-size simulation (that can be fit on
today's computers) with random initial conditions, it is *exceedingly*
unlikely that such a computer will exist anywhere in the domain.  But
for an *infinite* domain, the computer will exist here and there with
probability *unity*.  In fact, there will be some initial nonzero
density of these computers scattered throughout the domain.  Eventually,
their spheres of influence will grow.  As they do, perhaps they will
come into contact with each other.  Perhaps they will somehow "fight"
with each other.  In any event, they will certainly come to dominate the
asymptotics of the entire system.

Thus, in some sense, if an automaton in an infinite domain is capable of
universal computation, that will eventually be the most significant
thing determining its asymptotic state.

Is this observation at odds with what you are saying?  If not, why not?
If so, how do we resolve the two observations?

Thanks,
Bruce

From cellular-automata-request@Think.COM  Fri Oct  4 17:18:57 1991
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Date: Fri, 4 Oct 1991 17:19-0400
From: Allan C. Wechsler <ACW@YUKON.SCRC.Symbolics.COM>
Subject: phase transition and univ computation
To: bmb@Think.COM, liw@ROCKVAX.ROCKEFELLER.EDU
Cc: cellular-automata@Think.COM
In-Reply-To: <9110042034.AA12255@aldebaran.think.com>
Message-Id: <19911004211959.5.ACW@PALLANDO.SCRC.Symbolics.COM>

    Date: Fri, 4 Oct 1991 16:34 EDT
    From: Bruce Boghosian <bmb@Think.COM>

[Dr. Li said, in summary, that the universality of an automaton seems,
frequently, to have little impact on its observed dynamics.]

    There's something that I don't understand about this.

    If a particular CA can support a universal computer, then, with certain
    initial conditions, it can support a computer that is programmed to,
    say, clear out a vicinity, or perhaps somehow orgainize all the cells in
    that vicinity into nice neat rows of stable objects.  It might be a
    computer that organizes a given region in this way, and then moves on,
    trying to organize other regions similarly -- kind of a "combine" of
    sorts.

    Now I agree that for any finite-size simulation (that can be fit on
    today's computers) with random initial conditions, it is *exceedingly*
    unlikely that such a computer will exist anywhere in the domain.  But
    for an *infinite* domain, the computer will exist here and there with
    probability *unity*.  In fact, there will be some initial nonzero
    density of these computers scattered throughout the domain.  Eventually,
    their spheres of influence will grow.  As they do, perhaps they will
    come into contact with each other.  Perhaps they will somehow "fight"
    with each other.  In any event, they will certainly come to dominate the
    asymptotics of the entire system.

    Thus, in some sense, if an automaton in an infinite domain is capable of
    universal computation, that will eventually be the most significant
    thing determining its asymptotic state.

    Is this observation at odds with what you are saying?  If not, why not?
    If so, how do we resolve the two observations?

    Thanks,
    Bruce

I think Dr. Li's observations derive from observing real automata for
practical sizes and numbers of generations.  Yours, on the other hand,
is a theoretical musing about hyper-astronomical scales.  It's entirely
plausible that the smallest "smart" Life object in your sense is more
than 100 units on a side, and that it needs fairly wide spaces around it
devoid of Evil Influence in order for it to survive long enough to get
anything useful done.  If the resulting required configuration is, say,
1000 units on a side, then a million cells must be just right for the
smarty to get started reshaping the world.  The chances against this are
of course 2^(10^6), so one would expect to find one such smarty in a
square 2^(5x10^5) on a side.  We'd expect to start noticing the work of
such smarties in about that many generations.  The relevant numbers have
a couple of hundred thousand digits.

From bmb@Think.COM  Fri Oct  4 17:52:21 1991
Received: by mail.think.com; Fri, 4 Oct 91 17:52:44 -0400
Received: from Aldebaran.Think.COM by mail.think.com; Fri, 4 Oct 91 17:52:21 -0400
From: Bruce Boghosian <bmb@Think.COM>
Received: by aldebaran.think.com (4.1/Think-1.0C)
	id AA12300; Fri, 4 Oct 91 17:52:20 EDT
Date: Fri, 4 Oct 91 17:52:20 EDT
Message-Id: <9110042152.AA12300@aldebaran.think.com>
To: ACW@YUKON.SCRC.Symbolics.COM
Cc: liw@ROCKVAX.ROCKEFELLER.EDU, bmb@Think.COM, cellular-automata@Think.COM
In-Reply-To: Allan C. Wechsler's message of Fri, 4 Oct 1991 17:19-0400 <19911004211959.5.ACW@PALLANDO.SCRC.Symbolics.COM>
Subject: phase transition and univ computation


   Date: Fri, 4 Oct 1991 17:19-0400
   From: Allan C. Wechsler <ACW@YUKON.SCRC.Symbolics.COM>

   [...]

   I think Dr. Li's observations derive from observing real automata for
   practical sizes and numbers of generations.  Yours, on the other hand,
   is a theoretical musing about hyper-astronomical scales.  It's entirely
   plausible that the smallest "smart" Life object in your sense is more
   than 100 units on a side, and that it needs fairly wide spaces around it
   devoid of Evil Influence in order for it to survive long enough to get
   anything useful done.  If the resulting required configuration is, say,
   1000 units on a side, then a million cells must be just right for the
   smarty to get started reshaping the world.  The chances against this are
   of course 2^(10^6), so one would expect to find one such smarty in a
   square 2^(5x10^5) on a side.  We'd expect to start noticing the work of
   such smarties in about that many generations.  The relevant numbers have
   a couple of hundred thousand digits.

Interesting estimates.  I find it intriguing that such numbers come into
play in the analysis of the asymptotics of very simple dynamical
systems.

Thanks for the response!

--Bruce

From cellular-automata-request@Think.COM  Fri Oct  4 18:23:00 1991
Received: by mail.think.com; Fri, 4 Oct 91 18:23:09 -0400
Received: from Think.COM by mail.think.com; Fri, 4 Oct 91 18:23:00 -0400
Received: from YUKON.SCRC.Symbolics.COM by Early-Bird.Think.COM; Fri, 4 Oct 91 18:22:56 EDT
Received: from PALLANDO.SCRC.Symbolics.COM by YUKON.SCRC.Symbolics.COM via INTERNET with SMTP id 735405; 4 Oct 1991 18:21:08-0400
Date: Fri, 4 Oct 1991 18:23-0400
From: Allan C. Wechsler <ACW@YUKON.SCRC.Symbolics.COM>
Subject: phase transition and univ computation
To: bmb@Think.COM, ACW@YUKON.SCRC.Symbolics.COM
Cc: liw@ROCKVAX.ROCKEFELLER.EDU, cellular-automata@Think.COM
In-Reply-To: <9110042152.AA12300@aldebaran.think.com>
Message-Id: <19911004222357.6.ACW@PALLANDO.SCRC.Symbolics.COM>

    Date: Fri, 4 Oct 1991 17:52 EDT
    From: Bruce Boghosian <bmb@Think.COM>

    Interesting estimates.  I find it intriguing that such numbers come into
    play in the analysis of the asymptotics of very simple dynamical
    systems.

    Thanks for the response!

    --Bruce

The central question raised by all this is, why is /our/ universe so
small and so young?  We discussed this a while ago on this list, but I
think it bears repeating: there is something about the laws of our
universe that makes it qualitatively (read: quantitatively for an
extremely large quantity!) more hospitable to life than the Life
universe.

If we could guess what the crucial properties of our universe are, that
make the spontaneous creation of replicators so much more likely, then
we might be able to design a similarly more hospitable cellular rule.


From cellular-automata-request@Think.COM  Sat Oct  5 04:16:04 1991
Received: by mail.think.com; Sat, 5 Oct 91 04:16:06 -0400
Received: from Think.COM by mail.think.com; Sat, 5 Oct 91 04:16:04 -0400
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	id AA08578; Sat, 5 Oct 91 03:51:58 EDT
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	for ca@think.com (ca@think.com)
	(contact usenet@bloom-beacon.mit.edu if you have questions)
Date: 4 Oct 91 23:30:30 GMT
From: scott@ferrari.LABS.TEK.COM (Scott Huddleston)
Organization: Computer Research Laboratory, Tektronix, Inc., Beaverton OR
Subject: Re: phase transition and univ computation
Message-Id: <2748@crl.LABS.TEK.COM>
Newsgroups: comp.theory.cell-automata
References: <9110040359.AA14522@rocky7.rockefeller.edu>, <9110042034.AA12255@aldebaran.think.com>
Sender: ca-request@Think.COM
To: ca@Think.COM

In article <9110042034.AA12255@aldebaran.think.com> bmb@Think.COM (Bruce Boghosian) writes:
>If a particular CA can support a universal computer, then, with certain
>initial conditions, it can support a computer that is programmed to,
>say, clear out a vicinity, or perhaps somehow orgainize all the cells in
>that vicinity into nice neat rows of stable objects.  It might be a
>computer that organizes a given region in this way, and then moves on,
>trying to organize other regions similarly -- kind of a "combine" of
>sorts.

Universal computation doesn't imply the ability to, say, clear a vicinity.
It only implies the ability to "compute" any computable result
** using a particular encoding **.  All bets are off when you introduce
physical (or informational) variations from the encoding.

By analogy, a typical (universal) computer in real life can encode
results magnetically on tape, but it can't paint the tape green or
clean peanut butter off it.  Or a self-reproducing robot might be 
designed that can reproduce itself under a variety of environmental
variations, but not all possible environments:  things like particularly
nasty bombardments by the U.S. military or the sun going supernova
might disrupt an otherwise very robust self-reproducing robot.

It's a fascinating question whether a configuration in life could survive
in or clear an almost arbitrary environment.  But that's a separate question
from universality, and I haven't seen, read, or found any evidence that
such a configuration exists.
--
Scott Huddleston
scott@crl.labs.tek.com

From cellular-automata-request@Think.COM  Sun Oct  6 02:06:55 1991
Received: by mail.think.com; Sun, 6 Oct 91 02:07:03 -0400
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	id AA27199; Sun, 6 Oct 91 02:06:39 -0400
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	id AA17651; Sun, 6 Oct 91 02:06:35 EDT
Date: Sun, 6 Oct 91 02:06:35 EDT
From: liw@ROCKVAX.ROCKEFELLER.EDU (Wentian Li)
Message-Id: <9110060606.AA17651@rocky7.rockefeller.edu>
To: cellular-automata@Think.COM
Subject: Re: phase transition....


-------------------------------------------------------------------------
   Date: Fri, 4 Oct 1991 17:19-0400
   From: Allan C. Wechsler <ACW@YUKON.SCRC.Symbolics.COM>

   I think Dr. Li's observations derive from observing real automata for
   practical sizes and numbers of generations.  Yours, on the other hand,
   is a theoretical musing about hyper-astronomical scales.  It's entirely
   plausible that the smallest "smart" Life object in your sense is more
   than 100 units on a side, and that it needs fairly wide spaces around it
   devoid of Evil Influence in order for it to survive long enough to get
   anything useful done.  If the resulting required configuration is, say,
   1000 units on a side, then a million cells must be just right for the
   smarty to get started reshaping the world.  The chances against this are
   of course 2^(10^6), so one would expect to find one such smarty in a
   square 2^(5x10^5) on a side.  We'd expect to start noticing the work of
   such smarties in about that many generations.  The relevant numbers have
   a couple of hundred thousand digits.
--------------------------------------------------------------------------

I was not just talking about sizes. The point is more that
complex dynamics in "complex cellular automata" are emerged
automatically from almost all initial random conditions,
whereas the complex dynamics in a univeral computer can 
be just a result of a complex initial condition.  If this 
is the case, nothing is created by the rule, whatever
"interesting" behavior you see in the dynamics is purely
transformed from that special initial condition.

When the size is finite, those cellular automata that are
universal computers but not complex rules cannot get the
special initial condition necessary for an interesting
dynamics (because these special initial condition might
only appear in the infinite size limit). if we run these
rules from random initial conditions, we may only see
simple periodic or chaotic dynamics.

By this argument, cellular automata that are proved to be
universal computers is a larger set than the set of "complex
cellular automata" (class-4 rules, critical rules, etc..).
I cannot prove anything, for example, I do not know what
the percentage of "complex rules" is among all CAs that
are universal. There are other similar "vague" questions
which are difficult to answer because I cannot phrase them
precisely!

Wentian Li
Physics Department
Rockefeller University
1230 York Avenue
New York, NY 10021


From cellular-automata-request@Think.COM  Sun Oct  6 04:15:27 1991
Received: by mail.think.com; Sun, 6 Oct 91 04:15:30 -0400
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	id AA10499; Sun, 6 Oct 91 03:49:59 EDT
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	for ca@think.com (ca@think.com)
	(contact usenet@bloom-beacon.mit.edu if you have questions)
Date: Thu, 3 Oct 1991 19:23:21 GMT
From: shallit@graceland.uwaterloo.ca (Jeffrey Shallit)
Organization: University of Waterloo
Subject: grad schools for cellular automata
Message-Id: <1991Oct3.192321.18210@watserv1.waterloo.edu>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM

A friend is thinking about going to grad school and studying
cellular automata.  What are the good schools in North
America and Europe where this topic is studied?

Please reply by mail; I don't usually read this group.
If there is enough interest, I will summarize.

Jeff Shallit
shallit@graceland.waterloo.edu

From cellular-automata-request@Think.COM  Sun Oct  6 12:15:38 1991
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	id AA25910; Sun, 6 Oct 91 11:26:56 EDT
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Date: 6 Oct 91 14:51:03 GMT
From: heitkoet@gorbi.informatik.uni-dortmund.de (Joerg Heitkoetter)
Organization: University of Dortmund, Germany
Subject: Hodgepodge: the original...
Message-Id: <3865@laura.UUCP>
Newsgroups: comp.theory.cell-automata
References: <1991Sep23.182329.21471@cunews.carleton.ca>, <1546@isgtec.UUCP>, <3861@laura.UUCP>
Sender: ca-request@Think.COM
To: ca@Think.COM

Because I reached *some* requests for the original source, here it is.
Unfortunately I forgot to mention that all comments are in German. :-)
Well, let me know if this causes you grief...

And now, save this message to a file and use the "unshar" command;
that's all folks.

(C-Hacker's note: it was his first C program :-)

-------- cut here ---------------------------------------------------------
#!/bin/sh
# This is a shell archive (produced by shar 3.49)
# To extract the files from this archive, save it to a file, remove
# everything above the "!/bin/sh" line above, and type "sh file_name".
#
# made 10/06/1991 14:44 UTC by heitkoet@gorbi
# Source directory /home/lumpi/ls11d/heitkoet
#
# existing files will NOT be overwritten unless -c is specified
#
# This shar contains:
# length  mode       name
# ------ ---------- ------------------------------------------
#  12490 -rw-r----- infekt2.c
#
# ============= infekt2.c ==============
if test -f 'infekt2.c' -a X"$1" != X"-c"; then
	echo 'x - skipping infekt2.c (File already exists)'
else
echo 'x - extracting infekt2.c (Text)'
sed 's/^X//' << 'SHAR_EOF' > 'infekt2.c' &&
/****************************************************************/
/*                                                              */
/*             C-Textfile zum  INFEKTIONSMODELL                 */
/*                   von Martin Gerhardt                        */
/*                                                              */
/*  Version 2.0                                   31. 8. 1986   */
/*                                                              */
/*                                                              */
/*  Bemerkungen zur Art der Simulation:                         */
/*                                                              */
/*  - Rand des Feldes nicht geschlossen                         */
/*  - Moore-Nachbarschaft                                       */
/*  - einzulesende Feldgre sollte nicht grer als 179 sein   */
/*  - als Auswertung ist das Spielfeld dargestellt:             */
/*        - Tastaturbelegungen:                                 */
/*             'm' : Darstellung des Spielfeldes                */
/*             'B' : Beendigung der Simulation                  */
/*             'w' : Halt bis neuer Tastendruck erfolgt         */
/*             'E' : Neues Einlesen der Konstanten              */
/*                                                              */
/****************************************************************/
X
#ifdef __STD_C__			/* ATARI ST Turbo-C */
#include <aes.h>
#include <vdi.h>
#include <tos.h>
#include <stdio.h>
#else					/* Megamax-C */
#include <osbind.h>
#endif
X
int contrl[12], intin[128], ptsin[128], intout[128], ptsout[128];
X
int handle;
X
int work_out[57], work_in[12];
X
int set_mode, set_perimeter, set_color, set_interior, set_style, set_effect;
X
int Feldgr, Umschlagsgrenze, Infgeschw, k1, k2, Bgrad;
X
X
long Zufallszahl, Zeitpunkt, Umschlaege;
X
int *Feld, *Hfeld, *Krank, *Inf;
X
/*************************************************/
/*    open_work                                  */
/*************************************************/
X
open_work ()
{
X    int i;
X
X    appl_init ();
X    for (i = 0; i < 10; work_in[i++] = 1);
X    work_in[10] = 2;
X    v_opnvwk (work_in, &handle, work_out);
}
X
/*************************************************/
/*    close_work                                 */
/*************************************************/
X
close_work ()
{
X    gemdos (0x1);
X    v_clsvwk (handle);
X    appl_exit ();
}
X
/*************************************************/
/*   hide_mouse                                  */
/*************************************************/
static int hidden;
X
hide_mouse ()
{
X    if (!hidden) {
X	graf_mouse (256, 0x0L);
X	hidden = 1;
X    }
}
X
/**************************************************/
/*   show_mouse                                   */
/**************************************************/
show_mouse ()
{
X    if (hidden) {
X	graf_mouse (257, 0x0L);
X	hidden = 0;
X    }
}
X
/*************************************************/
/*    Speicherplatzreservierung                  */
/*************************************************/
Speicherplatz ()
{
X    if ((Feld = (int *) Malloc (2l * (long) Feldgr * (long) Feldgr)) == 0) {
X	form_alert (1, "[3][Speicherplatzmangel][Abbruch]");
X	return (1);
X    }
X    if ((Hfeld = (int *) Malloc (2l * (long) Feldgr * (long) Feldgr)) == 0) {
X	form_alert (1, "[3][Speicherplatzmangel][Abbruch]");
X	return (1);
X    }
X    if ((Inf = (int *) Malloc (2l * (long) Feldgr * (long) Feldgr)) == 0) {
X	form_alert (1, "[3][Speicherplatzmangel][Abbruch]");
X	return (1);
X    }
X    if ((Krank = (int *) Malloc (2l * (long) Feldgr * (long) Feldgr)) == 0) {
X	form_alert (1, "[3][Speicherplatzmangel][Abbruch]");
X	return (1);
X    }
X    return (0);
}
X
/*************************************************/
/*    Speicherplatzfreigabe                      */
/*************************************************/
Speicherfrei ()
{
X    Mfree (Feld);
X    Mfree (Hfeld);
X    Mfree (Krank);
X    Mfree (Inf);
}
X
/*************************************************/
/*    Zufallszahl                                */
/*************************************************/
X
#define M 100000000
#define m1  10000L
#define b 31415821
X
long
Multiply (p, q)
X    long p, q;
X
{
X    long p0, p1, q0, q1;
X
X    p1 = p / m1;
X    p0 = p % m1;
X    q1 = q / m1;
X    q0 = q % m1;
X
X    return ((((p0 * q1 + p1 * q0) % m1) * m1 + p0 * q0) % M);
}
X
X
rnd (maxvalue)
X    long maxvalue;
X
{
X    long Multiply ();
X
X    Zufallszahl = (Multiply (Zufallszahl, b) + 1L) % M;
X    return ((((Zufallszahl / m1) * maxvalue) / m1) % 65536);
}
X
X
/*************************************************/
/*  Einlesen                                     */
/*************************************************/
X
Einlesen ()
{
X    do {
X
X	v_clrwk (handle);
X	printf ("\033H\033e");
X	printf ("Feldgre = ");
X	scanf ("%d", &Feldgr);
X	Feldgr = Feldgr + 2;
X	printf ("Umschlagsgrenze = ");
X	scanf ("%d", &Umschlagsgrenze);
X	printf ("Infektionsgeschw. = ");
X	scanf ("%d", &Infgeschw);
X	printf ("k1 = ");
X	scanf ("%d", &k1);
X	printf ("k2 = ");
X	scanf ("%d", &k2);
X	printf ("Bedeckungsgrad = ");
X	scanf ("%d", &Bgrad);
X	printf ("Zufallszahl = ");
X	scanf ("%ld", &Zufallszahl);
X	printf ("\033f");
X
X	printf ("\n\n\n    continue   (y/n)\n");
X    }
X    while ((char) evnt_keybd () != 'y');
}
X
/********************************************/
/*   Anfangsbelegung                        */
/********************************************/
X
Anfangsbelegung ()
{
X    register int i, j;
X
X    for (i = 1; i <= Feldgr - 2; i++)
X	for (j = 1; j <= Feldgr - 2; j++) {
X
X	    if (rnd (100L) >= Bgrad)
X		*(Feld + i * Feldgr + j) = 0;
X	    else
X		*(Feld + i * Feldgr + j) = rnd ((long) Umschlagsgrenze);
X	    *(Hfeld + i * Feldgr + j) = 0;
X	}
X
X    for (i = 0; i <= Feldgr - 1; i++) {
X	*(Feld + i) = -1;
X	*(Feld + i * Feldgr) = -1;
X	*(Feld + (i + 1) * Feldgr - 1) = -1;
X	*(Feld + Feldgr * (Feldgr - 1) + i) = -1;
X
X	*(Hfeld + i) = -1;
X	*(Hfeld + i * Feldgr) = -1;
X	*(Hfeld + (i + 1) * Feldgr - 1) = -1;
X	*(Hfeld + Feldgr * (Feldgr - 1) + i) = -1;
X    }
}
X
/*****************************/
/* Hilfsfeldneu              */
/*****************************/
Hfeldneu ()
{
X    register int i, j;
X
X    for (i = 1; i <= Feldgr - 2; i++)
X	for (j = 1; j <= Feldgr - 2; j++)
X	    *(Hfeld + i * Feldgr + j) = 0;
}
X
/********************************************/
/*   grafische Auswertung                   */
/********************************************/
X
/*****************************/
/* Grafiktext                */
/*****************************/
Text ()
{
X    char string[50];
X
X    v_gtext (handle, 410, 20, "************************");
X    v_gtext (handle, 410, 40, "*   Infektionsmodell   *");
X    v_gtext (handle, 410, 60, "************************");
X    v_gtext (handle, 410, 80, " - Moore Nachbarschaft ");
X    v_gtext (handle, 410, 100, " - Feld mit Rand        ");
X    set_effect = vst_effects (handle, 8);
X    v_gtext (handle, 410, 130, "Konstanten :");
X    v_gtext (handle, 410, 300, "Berechnung :");
X    set_effect = vst_effects (handle, 0);
X    sprintf (string, "  Feldgroesse       : %d", Feldgr - 2);
X    v_gtext (handle, 410, 150, string);
X    sprintf (string, "  Umschlagsgrenze   : %d", Umschlagsgrenze);
X    v_gtext (handle, 410, 170, string);
X    sprintf (string, "  Infektionsgeschw. : %d", Infgeschw);
X    v_gtext (handle, 410, 190, string);
X    sprintf (string, "  k1 (krank)        : %d", k1);
X    v_gtext (handle, 410, 210, string);
X    sprintf (string, "  k2 (infiziert)    : %d", k2);
X    v_gtext (handle, 410, 230, string);
X    sprintf (string, "  Bedeckungsgrad    : %d", Bgrad);
X    v_gtext (handle, 410, 250, string);
X    sprintf (string, "  Zufallszahl       : %ld", Zufallszahl);
X    v_gtext (handle, 410, 270, string);
X    v_gtext (handle, 410, 320, "  Zeitpunkt  : ");
X    v_gtext (handle, 410, 340, "  Umschlaege : ");
}
X
/*****************************/
/* Setze Attribute           */
/*****************************/
X
Setze_Attribute ()
{
X    set_mode = vswr_mode (handle, 1);
X    set_perimeter = vsf_perimeter (handle, 0);
X    set_color = vsf_color (handle, 1);
}
X
/*****************************/
/* Hintergrund : schwarz     */
/*****************************/
X
Hintergrund ()
{
X    int pxyarray[4];
X
X    pxyarray[0] = 0;
X    pxyarray[1] = 0;
X    pxyarray[2] = (400 / (Feldgr - 2)) * (Feldgr - 2);
X    pxyarray[3] = (400 / (Feldgr - 2)) * (Feldgr - 2);
X
X    set_interior = vsf_interior (handle, 1);
X
X    vr_recfl (handle, pxyarray);
}
X
/*****************************/
/* welcher Farbwert ?        */
/*****************************/
X
Farbe (z)
X    int z;
X
{
X    switch (z) {
X
X	case -1:
X	case 0:
X	    return (8);
X	    break;
X	default:
X	    if (z >= Umschlagsgrenze)
X		return (0);
X	    else
X		return (7 - ((7 * z) / Umschlagsgrenze));
X	    break;
X    }
}
X
/*****************************/
/* Zeichne Rechteck          */
/*****************************/
X
Fill_Rectangle (x, y, Schritt, style)
X    int x, y, Schritt, style;
X
{
X    int pxyarray[4];
X
X    pxyarray[0] = (y - 1) * Schritt;
X    pxyarray[1] = (x - 1) * Schritt;
X    pxyarray[2] = y * Schritt;
X    pxyarray[3] = x * Schritt;
X
X    switch (style) {
X
X	case 0:
X	    set_interior = vsf_interior (handle, 0);
X	    vr_recfl (handle, pxyarray);
X	    break;
X	default:
X	    set_interior = vsf_interior (handle, 2);
X	    set_style = vsf_style (handle, style);
X	    vr_recfl (handle, pxyarray);
X	    break;
X    }
}
X
/************************/
/* Auswertfunktion      */
/************************/
X
Auswertung ()
{
X    register int i, j;
X    int style, Schritt;
X
X    Schritt = 400 / (Feldgr - 2);
X
X    for (i = 1; i <= Feldgr - 2; i++)
X	for (j = 1; j <= Feldgr - 2; j++)
X	    if ((style = Farbe (*(Feld + i * Feldgr + j))) != Farbe (*(Hfeld + i
* Feldgr + j)))
X		Fill_Rectangle (i, j, Schritt, style);
}
X
/********************************************/
/*    Rekursionsgleichung                   */
/********************************************/
X
Hilfsfelder ()
{
X    register int i, j;
X
X    for (i = 0; i < Feldgr; i++)
X	for (j = 0; j < Feldgr; j++) {
X
X	    *(Krank + i * Feldgr + j) = 0;
X	    *(Inf + i * Feldgr + j) = 0;
X
X	    if (*(Feld + i * Feldgr + j) >= Umschlagsgrenze)
X		*(Krank + i * Feldgr + j) = 1;
X	    else if (*(Feld + i * Feldgr + j) > 0)
X		*(Inf + i * Feldgr + j) = 1;
X	}
}
X
Rekursion ()
{
X    register int i, j, ni, nj;
X    int krank, infiziert, infsumme;
X    int *ptr;
X
X    Zeitpunkt = Zeitpunkt + 1l;
X    Umschlaege = 0;
X
X    Hilfsfelder ();
X
X    for (i = 1; i <= Feldgr - 2; i++)
X	for (j = 1; j <= Feldgr - 2; j++) {
X
X	    switch (*(Feld + i * Feldgr + j)) {
X
X		case 0:
X		    krank = 0;
X		    infiziert = 0;
X
X		    for (ni = -1; ni <= 1; ni++)
X			for (nj = -1; nj <= 1; nj++) {
X			    krank = krank + *(Krank + (i + ni) * Feldgr + j + nj);
X			    infiziert = infiziert + *(Inf + (i + ni) * Feldgr + j + nj);
X			}
X		    *(Hfeld + i * Feldgr + j) = krank / k1 + infiziert / k2;
X		    break;
X
X		default:
X		    if (*(Feld + i * Feldgr + j) >= Umschlagsgrenze) {
X			*(Hfeld + i * Feldgr + j) = 0;
X			Umschlaege = Umschlaege + 1;
X		    } else {
X			infsumme = 0;
X			infiziert = 0;
X
X			for (ni = -1; ni <= 1; ni++)
X			    for (nj = -1; nj <= 1; nj++) {
X				infsumme = infsumme + (*(Inf + (i + ni) * Feldgr + j + nj)
X				      * *(Feld + (i + ni) * Feldgr + j + nj));
X
X				infiziert = infiziert + *(Inf + (i + ni) * Feldgr + j + nj);
X			    }
X			*(Hfeld + i * Feldgr + j) = infsumme / infiziert + Infgeschw;
X		    }
X		    break;
X	    }
X	}				/* rekursive Schleife */
X
X /* Kopie */
X    ptr = Hfeld;
X    Hfeld = Feld;
X    Feld = ptr;
X
}					/* Ende */
X
/*******************************************************/
main ()
{
X    char ch;
X    char string[50];
X
X    open_work ();
X    hide_mouse ();
X    Einlesen ();
X    if (Speicherplatz () == 1)
X	goto ENDE;
X    Setze_Attribute ();
X    v_clrwk (handle);
X    Hintergrund ();
X    Text ();
X    Anfangsbelegung ();
X    Auswertung ();
X    ch = (char) evnt_keybd ();
X    Zeitpunkt = 0l;
X
X    while (ch != 'B') {
X	Rekursion ();
X	if (Cconis () != 0) {
X	    ch = Crawcin ();
X	    if (ch == 'm') {
X		Hintergrund ();
X		Hfeldneu ();
X	    }
X	}
X	if (ch == 'w')
X	    ch = (char) evnt_keybd ();
X	sprintf (string, "%ld", Zeitpunkt);
X	v_gtext (handle, 530, 320, string);
X	sprintf (string, "%ld    ", Umschlaege);
X	v_gtext (handle, 530, 340, string);
X	if (ch == 'm')
X	    Auswertung ();
X	if (ch == 'E') {
X	    Einlesen ();
X	    v_clrwk (handle);
X	    Hintergrund ();
X	    Text ();
X	    Hfeldneu ();
X	    ch = 'm';
X	}
X    }
X    Speicherfrei ();
X    show_mouse ();
ENDE:close_work ();
}
SHAR_EOF
chmod 0640 infekt2.c ||
echo 'restore of infekt2.c failed'
Wc_c="`wc -c < 'infekt2.c'`"
test 12490 -eq "$Wc_c" ||
	echo 'infekt2.c: original size 12490, current size' "$Wc_c"
fi
exit 0
------------------------------------------------------------------------

Enjoy!

	-joke

--
Joerg Heitkoetter
Systems Analysis Group
University of Dortmund, Germany
(heitkoet@gorbi.informatik.uni-dortmund.de).

From cellular-automata-request@Think.COM  Sun Oct  6 16:15:31 1991
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Date: 6 Oct 91 23:02:34 GMT
From: aboulang@bbn.com (Albert Boulanger)
Organization: BBN, Cambridge MA
Subject: Re: phase transition and univ computation
Message-Id: <ABOULANG.91Oct6160234@kariba.bbn.com>
Newsgroups: comp.theory.cell-automata
References: <9110042152.AA12300@aldebaran.think.com>
Sender: ca-request@Think.COM
To: ca@Think.COM

In article <19911004222357.6.ACW@PALLANDO.SCRC.Symbolics.COM> ACW@YUKON.SCRC.Symbolics.COM
(Allan C. Wechsler) writes:

   The central question raised by all this is, why is /our/ universe so
   small and so young?  We discussed this a while ago on this list, but I
   think it bears repeating: there is something about the laws of our
   universe that makes it qualitatively (read: quantitatively for an
   extremely large quantity!) more hospitable to life than the Life
   universe.

   If we could guess what the crucial properties of our universe are, that
   make the spontaneous creation of replicators so much more likely, then
   we might be able to design a similarly more hospitable cellular rule.

In my mind this robustness to life is tied with the question of the
*emergence* of a thermodynamic arrow to time in nature with reversible
micro-laws. My thesis is that we are going to have a hard time
simulating this arrow-of-time emergence on stationary-environment
cellular automata models. Nobody has solved the arrow of time problem
yet, but I suspect there is something in Mackey's second possibility in:

"The Dynamic Origin of Increasing Entropy"
Michael Mackey
Rev. of Modern Physics, Vol 61, No 4, Oct 1989, 981-1015

which is that the system is coupled to an external heat-bath.  (The
first is coarse graining.) What I think is happening is that nature has
a source (implicit in the heat bath) of high quality algorithmic
complexity numbers. The nature machine just grinds through these
numbers producing times arrow and its dual, evolving structure (under
the right rules, of course). I am interested in asynchronous cellular
automata with self-clocked cells for this reason. I want my system to
be coupled to a heat bath and this is one way of doing it.


An organism in a heat (flame?) bath,
Albert Boulanger
aboulanger@bbn.com

From cellular-automata-request@Think.COM  Mon Oct  7 08:04:09 1991
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Date: 6 Oct 91 15:04:13 GMT
From: shallit@graceland.uwaterloo.ca (Jeffrey Shallit)
Organization: University of Waterloo
Subject: grad schools for cellular automata?
Message-Id: <1991Oct6.150413.17814@watserv1.waterloo.edu>
Newsgroups: sci.math,comp.theory,comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM

Since I've gotten no responses from my first query,
I'm casting my net a bit wider this time.

A friend is interesting in doing a Ph. D. on cellular
automata.  Can anyone recommend the appropriate graduate
schools in North America or Europe where cellular
automata is an active research topic?

Thanks for your help,

Jeff Shallit
shallit@graceland.waterloo.edu

From cellular-automata-request@Think.COM  Tue Oct  8 23:07:05 1991
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Date: Wed, 9 Oct 1991 01:56:02 GMT
From: shallit@graceland.uwaterloo.ca (Jeffrey Shallit)
Organization: University of Waterloo
Subject: graduate schools for cellular automata
Message-Id: <1991Oct9.015602.20913@watserv1.waterloo.edu>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM

Thanks to all who responded to my query about graduate schools
for studying cellular automata.  Here's a summary of the responses:


From: sipser@math.mit.edu 

	There is a group (led by Toffoli) here at MIT which is building
	a cellular automaton simulator (ultra high capacity) and has
	done some work on theory, etc.  I am not sure if they
	take on any students, or how their work is viewed in the 
	CA community.  Your friend may wish to contact them to get
	more info.


From mroussel@alchemy.chem.utoronto.ca

     Cellular automata are used in a wide variety of contexts.  You
didn't say if your friend is interested in the physical sciences,
computer science, or something else entirely.  If your friend is
interested in applications of cellular automata to the physical
sciences, I can think of no finer place for him to study than right here
in the chemistry department at the University of Toronto.  Profs. Kapral
and Fraser both work in this area.  Prof. Fraser is interested in
cellular automata on lattices with interesting connectivity (fractals
for instance).  Prof. Kapral uses lattice gas automata to model chemical
dynamics.  Rather than take my word for it, you should have your friend
email these fellows for more information.  Prof. Fraser is
sfraser@alchemy.chem.utoronto.ca and Prof. Kapral is
rkapral@alchemy.chem.utoronto.ca.


From bmb@Think.COM:

If your friend is looking for work on pure CA, then Toffoli and
Margolus' group at MIT's Laboratory for Computer Science comes to mind.
If he's interested in studying lattice gases (CA fluids), however, there
are many more possibilities.

Bruce Boghosian


From kurt@Think.COM:

Here are some places to think about:

1) Univ Illinois - Norm Packard is there.  He's done work on CA's (as well
as chaos and GA's) in the past and currently has students working in those
areas.

2) Univ Penn - Stuart Kauffman is there.  He's done work in random boolean
nets (which are related to CA's).

3) Boston University - Peter Gacs is there.  He's worked on reliable CA's.
Also Gene Stanley is there working on condensed matter physics and ising
models (both are on the physics side of CA's).  Ed Fredkin's also there.

4) MIT - The information mechanics group has Tom Toffoli and Norm Margulis.

5) UC Berkeley - Jim Crutchfield is there (but I don't know if he is planning
on staying permanently).

Another possibility is to go someplace good (but not someplace known for CA's).
Then find an advisor who is willing to let you do what you want.  Then
get a graduate research position at Los Alamos National Lab.  Go to LANL and
do your work (they have some very good people including Erica Jen and Chris
Lanton).  Then go back to your university and defend your dissertation. I know
of one person who is doing this.

You should look through the literature (say PHYSICA 45D, which is a special
issue on CA's) to see if there is anyone who's work interests you.


From rwt@ohm.york.ac.uk:

We are currently doing a fair amount of work with CA,
both in the "pure" sense - basic theory etc.., and in
the applied sense - our OS kernel for parallel machines
is heavily influenced by CA phenomena and we have a custom
CA machine - the FAMe (fuzzy automata machine) that is being used
for logic testing, physical modelling and neural net simulation.

Richard

* Dr R W Taylor              tel : (44) 904 432351  fax : 432335 *
* Adaptive Systems Group     email : rwt@uk.ac.york.ohm          *
* University of York, England                                    *



From sundar@gargoyle.uchicago.edu:

Karel Culik at the University of South Carolina works on
cellular automata.
-Sundar.



From jbaez@math.mit.edu 

The Physics of Computation group at MIT is one of the hottest places
for cellular automata... they're working on building CAM 8, a dedicated
Cellular Automaton Machine.  The leader of the group is Tomasso Toffoli.
I'll send you the email address of a friend of mine in that group.

My friend's name is Mark Smith and he's at smith@im.lcs.mit.edu.

John Baez



From brian@theory.lcs.mit.edu :

Tom Toffoli's group at MIT's Lab for Computer Science is doing cellular
automata (I think with some physics applications.) The group's not
particularly large, but it's probably a great environment for a grad
student since I suspect there are more faculty/postdocs/research scientists
than grads. On the other hand I really don't know anyone in the group
except socially, so I can't really say too much about the research.
Good Luck.  -Brian



From minch@lotka.Stanford.EDU: 

I can only recommend my own alma mater, the Systems Science  
Department of the Watson School at State University of New York,  
Binghamton. There you can encounter George Klir, who treats cellular  
automata (and other discrete models) from a formal perspective,  
Howard Pattee, who is interested in them as models for theoretical  
biology, and Narendra Goel, who uses them in applications related to  
cellular morphogenesis.

*  Eric Minch              
*  minch@lotka.stanford.edu


From bern@parc.xerox.com 

Jeff,

An erstwhile chaos theorist here (Scott Shenker) says
that the Complex Systems Center (or something like that)
at U. of Illinois is the place.  Steven Wolfram was
still doing cellular automata last Scott heard. 

Regards,
 Marshall Bern


 
From scavo@cie.uoregon.edu 

Yes, there is a one David Griffeath (sp?) at Wisconsin who
is into this.  He did a recent _Notices_ article that I
can look up for you, if you wish.

Tom Scavo
scavo@cie.uoregon.edu



From klinger%saturn@sdsu.edu 

This is an interesting question.  I am interested in physics and cellular
automata, so I can give you one example at least.  MIT has an information
mechanics group including Norman Margolus and Tommaso Toffoli, who have
marketed a "cellular automata for PCs" board which they use in their book
to do simulations.

Toffoli is the author of "Cellular Automata as a substitute for (rather than 
a simulation of) differential equations in modeling physical laws," in a 
1984 issue of Physica D devoted to cellular automata
(I may not have the title of the article quite right).

Also, I would check out that issue of Physica D and look up some of the names
in there.  If you could inform me of the net response I would appreciate it,
since I am considering a thesis on the same subject.




From cellular-automata-request@Think.COM  Wed Oct  9 16:04:41 1991
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Date: 9 Oct 91 17:57:10 GMT
From: klinger@saturn.sdsu.edu (Andrew Klinger)
Organization: San Diego State University, Math Dept.
Subject: Re: phase transition and univ computation
Message-Id: <1991Oct9.175710.24188@sciences.sdsu.edu>
Newsgroups: comp.theory.cell-automata
References: <9110040359.AA14522@rocky7.rockefeller.edu>, <9110042034.AA12255@aldebaran.think.com>
Sender: ca-request@Think.COM
To: ca@Think.COM

>density of these computers scattered throughout the domain.  Eventually,
>their spheres of influence will grow.  As they do, perhaps they will
>come into contact with each other.  Perhaps they will somehow "fight"
>with each other.  In any event, they will certainly come to dominate the
>asymptotics of the entire system.

>Is this observation at odds with what you are saying?  If not, why not?
>If so, how do we resolve the two observations?
>Bruce

Hurray!  The Fermi Paradox for CA!

--Andrew 

From cellular-automata-request@Think.COM  Thu Oct 10 14:37:47 1991
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	id AA16233; Thu, 10 Oct 91 14:37:21 EDT
Date: Thu, 10 Oct 91 14:37:21 EDT
From: hoey@AIC.NRL.Navy.Mil (Dan Hoey)
Message-Id: <9110101837.AA16233@Sun0.AIC.NRL.Navy.Mil>
To: Bruce Boghosian <bmb@Think.COM>
Cc: ca@Think.COM
Subject: Re: phase transition and univ computation
In-Reply-To: <1991Oct9.175710.24188@sciences.sdsu.edu>
References: <9110040359.AA14522@rocky7.rockefeller.edu>, <9110042034.AA12255@aldebaran.think.com>
Organization: Navy Center for Applied Research in AI

Bruce Boghosian <bmb@Think.COM> writes:

> If a particular CA can support a universal computer, then, with certain
> initial conditions, it can support a computer that is programmed to,
> say, clear out a vicinity, or perhaps somehow organize all the cells in
> that vicinity into nice neat rows of stable objects....

> ... for an *infinite* domain...there will be some initial nonzero
> density of these computers scattered throughout the domain.  Eventually,
> their spheres of influence will grow....

The problem with this is that the the destructive forms may be more
virulent than the organized ones.  To make this concrete, consider the
CA that runs Life on just the red (or just the black) squares of a
checkerboard, but when faced with live cells of opposite parity in its
neighborhood, becomes unconditionally alive.  This CA is universal,
since it can run Life if programmed properly.  But in a randomized
starting position, the white goo will propagate from all but the
sparsest regions at velocity 1.  The lifespan of any universal regions
will be a random variable with exponential dropoff.

A few months ago I tried to make a similar argument that the
0xx->00/1xx->1101 tag system was probably nonuniversal because it
usually died out quickly.  But the argument just doesn't hold water.
Also, Mike Robson <jmr@anucsd.anu.edu.oz> informs me that the string
consisting of 330 1's runs for more than 10^13 steps before
terminating, based on a ten-month computer simulation he ran.

Dan Hoey
Hoey@AIC.NRL.Navy.Mil

From cellular-automata-request@Think.COM  Thu Oct 10 18:43:51 1991
Received: by mail.think.com; Thu, 10 Oct 91 18:44:05 -0400
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Date: Thu, 10 Oct 1991 18:45-0400
From: Allan C. Wechsler <ACW@YUKON.SCRC.Symbolics.COM>
Subject: Re: phase transition and univ computation
To: hoey@AIC.NRL.Navy.Mil, bmb@Think.COM
Cc: ca@Think.COM
In-Reply-To: <9110101837.AA16233@Sun0.AIC.NRL.Navy.Mil>
Message-Id: <19911010224525.5.ACW@PALLANDO.SCRC.Symbolics.COM>

    Date: Thu, 10 Oct 1991 14:37 EDT
    From: hoey@AIC.NRL.Navy.Mil (Dan Hoey)

    Bruce Boghosian <bmb@Think.COM> writes:

    > If a particular CA can support a universal computer, then, with certain
    > initial conditions, it can support a computer that is programmed to,
    > say, clear out a vicinity, or perhaps somehow organize all the cells in
    > that vicinity into nice neat rows of stable objects....

    > ... for an *infinite* domain...there will be some initial nonzero
    > density of these computers scattered throughout the domain.  Eventually,
    > their spheres of influence will grow....

    The problem with this is that the the destructive forms may be more
    virulent than the organized ones.  To make this concrete, consider the
    CA that runs Life on just the red (or just the black) squares of a
    checkerboard, but when faced with live cells of opposite parity in its
    neighborhood, becomes unconditionally alive.  This CA is universal,
    since it can run Life if programmed properly.  But in a randomized
    starting position, the white goo will propagate from all but the
    sparsest regions at velocity 1.  The lifespan of any universal regions
    will be a random variable with exponential dropoff.

This counterexample is bloody brilliant, and crystallizes something that
has been bothering me about the premise that "smarties" will eventually
take over any randomly initialized universal CA, provided it's big
enough.

The point is that the Life rule itself may be volatile enough to do in
any smarties that get fortuitously created at T=0.

The relevant challenge is this: you have to design a configuration that
fits inside a rectangle.  You can, of course, predict the contents of
any inset rectangle for as far in the future as it takes light to reach
the inset from the border.  The challenge is, to predict the contents of
an inset rectangle farther in the future than that.  Once you have made
your prediction, I get to put anything I want outside the outer
rectangle, to try to violate your prediction.

You may be able to defend yourself for a few generations, but my guess
is that Life does not contain any really strong fortresses.

    A few months ago I tried to make a similar argument that the
    0xx->00/1xx->1101 tag system was probably nonuniversal because it
    usually died out quickly.  But the argument just doesn't hold water.
    Also, Mike Robson <jmr@anucsd.anu.edu.oz> informs me that the string
    consisting of 330 1's runs for more than 10^13 steps before
    terminating, based on a ten-month computer simulation he ran.

    Dan Hoey
    Hoey@AIC.NRL.Navy.Mil


From cellular-automata-request@Think.COM  Thu Oct 10 21:06:26 1991
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Date: 10 Oct 91 23:41:09 GMT
From: scott@ferrari.LABS.TEK.COM (Scott Huddleston)
Organization: Computer Research Laboratory, Tektronix, Inc., Beaverton OR
Subject: Re: phase transition and univ computation
Message-Id: <2794@crl.LABS.TEK.COM>
Newsgroups: comp.theory.cell-automata
References: <9110101837.AA16233@Sun0.AIC.NRL.Navy.Mil>, <19911010224525.5.ACW@PALLANDO.SCRC.Symbolics.COM>
Sender: ca-request@Think.COM
To: ca@Think.COM

In article <19911010224525.5.ACW@PALLANDO.SCRC.Symbolics.COM> ACW@YUKON.SCRC.Symbolics.COM (Allan C. Wechsler) writes:
>The relevant challenge is this: you have to design a configuration that
>fits inside a rectangle.  You can, of course, predict the contents of
>any inset rectangle for as far in the future as it takes light to reach
>the inset from the border.  The challenge is, to predict the contents of
>an inset rectangle farther in the future than that.  Once you have made
>your prediction, I get to put anything I want outside the outer
>rectangle, to try to violate your prediction.
>
>You may be able to defend yourself for a few generations, but my guess
>is that Life does not contain any really strong fortresses.

I share your conjecture that Life does not contain any really strong 
fortresses, but I have to quibble over the encroachment rate.

You seem to saying that information outside an initial rectangle
can propagate thru the rectangle at the speed of light, regardless
of the rectangle contents.  

I bet there are doubly-periodic Life configurations whose restrictions
to a rectangle limit encroachment from arbitrary outside configurations
to some fraction f of the speed of light.  (I'm talking standard Life
rules here, not arbitrary 2-state 2-dimensional Moore neighborhood
automata).  I expect also that constructing such configurations with
f provably < 1 is tractable, and it would be interesting to explore
how provably small f can be.
--
Scott Huddleston
scott@crl.labs.tek.com

From hiebeler@Think.COM  Fri Oct 11 08:15:17 1991
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Cc: hoey@AIC.NRL.Navy.Mil, bmb@Think.COM, ca@Think.COM
In-Reply-To: Allan C. Wechsler's message of Thu, 10 Oct 1991 18:45-0400 <19911010224525.5.ACW@PALLANDO.SCRC.Symbolics.COM>
Subject: phase transition and univ computation



> From: Allan C. Wechsler <ACW@YUKON.SCRC.Symbolics.COM>
> 
> The relevant challenge is this: you have to design a configuration that
> fits inside a rectangle.  You can, of course, predict the contents of
> any inset rectangle for as far in the future as it takes light to reach
> the inset from the border.  The challenge is, to predict the contents of
> an inset rectangle farther in the future than that.  Once you have made
> your prediction, I get to put anything I want outside the outer
> rectangle, to try to violate your prediction.


  I think Fredkin once said something about irresistible forces and
immovable objects in cellular automata (someone please correct me if
I'm misremembering this).  I believe the reasoning was something like
"you cannot have a truly irresistible force or entity in a CA, because
if you did, what would happen if you made two copies of the thing, and
pitted them against each other?"

  The argument doesn't directly apply to fortresses, but it points out
that you can't win a similar challenge, namely "design a moving
object, and I will try to design something to stop it.  Can you build
something that I cannot stop?"  All I would have to do to win is build
the same thing you did, and point it at yours.

--
Dave Hiebeler                  | Internet: hiebeler@think.com
Thinking Machines Corporation  | UUCP: {uunet,harvard}!think!hiebeler
245 First Street               | Bitnet: hiebeler%think.com@mitvma.bitnet
Cambridge, MA 02142  USA       | Phone:  (617) 234-4070 (work)

From cellular-automata-request@Think.COM  Sat Oct 12 03:09:48 1991
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Date: 12 Oct 91 02:43:43 GMT
From: bennett@mp.cs.niu.edu (Scott Bennett)
Organization: Northern Illinois University
Subject: Re: phase transition and univ computation
Message-Id: <1991Oct12.024343.18861@mp.cs.niu.edu>
Newsgroups: comp.theory.cell-automata
References: <9110101837.AA16233@Sun0.AIC.NRL.Navy.Mil>, <19911010224525.5.ACW@PALLANDO.SCRC.Symbolics.COM>
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To: ca@Think.COM

In article <19911010224525.5.ACW@PALLANDO.SCRC.Symbolics.COM> ACW@YUKON.SCRC.Symbolics.COM (Allan C. Wechsler) writes:
>
>    [text deleted  --SJB]
>
>The relevant challenge is this: you have to design a configuration that
>fits inside a rectangle.  You can, of course, predict the contents of
>any inset rectangle for as far in the future as it takes light to reach
>the inset from the border.  The challenge is, to predict the contents of
>an inset rectangle farther in the future than that.  Once you have made
>your prediction, I get to put anything I want outside the outer
>rectangle, to try to violate your prediction.
>
     Perhaps I'm missing your point, but the issue of predictability
would seem to be fairly basic here.  Anytime propagating information
can appear unpredictably at the edge of such a domain, the predicta-
bility of an inset is, in principle, limited to a time determined by
the distance over which the propagation must occur to reach the inset
divided by the propagation velocity (N.B. velocity is a vector, not
a scalar.)
     Now, it *may* turn out that the challenge you suggest is not
always pointless.  In some kinds of systems, e.g. weather models,
the predictability may be preserved at a practical level in certain
situations.  People involved in synoptic forecasting models are
studying effects of chaos in their models and have come up with
some interesting ways of determining whether a given forecast run's
output is likely to be reliable.  Some variant of their techniques
may prove to be good for dealing with situations involving unpredic-
table boundary conditions.
     For the time being, though, the forecasts for much of the left
coast of North America will be reliable out to much shorter future
times than for areas farther east because of the lack of data about
the effects propagating in from the west (i.e. data density drops
to nearly zero over the Pacific.)  Because propagation is primarily
westerly, it takes much longer for an effect to reach the eastern
part of the domain from the edge where it entered, so an eastern
inset usually is predictable out to much farther in the future than
a western inset, even if the eastern inset is closer to an edge of
the rectangular domain.


                                  Scott Bennett, Comm. ASMELG, CFIAG
                                  Systems Programming
                                  Northern Illinois University
                                  DeKalb, Illinois 60115
**********************************************************************
* Internet:       bennett@cs.niu.edu                                 *
* BITNET:         A01SJB1@NIU                                        *
*--------------------------------------------------------------------*
*  "...And the heat came round and busted me                         *
*      For smilin' on a cloudy day!                                  *
*      Coming, coming, coming around..."                             *
**********************************************************************

From cellular-automata-request@Think.COM  Sat Oct 12 04:07:53 1991
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Date: 12 Oct 91 04:11:11 GMT
From: bennett@mp.cs.niu.edu (Scott Bennett)
Organization: Northern Illinois University
Subject: Re: phase transition and univ computation
Message-Id: <1991Oct12.041111.8390@mp.cs.niu.edu>
Newsgroups: comp.theory.cell-automata
References: <9110101837.AA16233@Sun0.AIC.NRL.Navy.Mil>, <19911010224525.5.ACW@PALLANDO.SCRC.Symbolics.COM>, <1991Oct12.024343.18861@mp.cs.niu.edu>
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In article <1991Oct12.024343.18861@mp.cs.niu.edu> I wrote:
>In article <19911010224525.5.ACW@PALLANDO.SCRC.Symbolics.COM> ACW@YUKON.SCRC.Symbolics.COM (Allan C. Wechsler) writes:
>>
>>    [text deleted  --SJB]
>>
>     Perhaps I'm missing your point, but the issue of predictability
>would seem to be fairly basic here.  Anytime propagating information
>can appear unpredictably at the edge of such a domain, the predicta-
>bility of an inset is, in principle, limited to a time determined by
>the distance over which the propagation must occur to reach the inset
>divided by the propagation velocity (N.B. velocity is a vector, not
>a scalar.)

     Oops.
     That should have been "...divided by the dot product of the propa-
gation velocity and the vector from the point of entry at the edge to
the inset."  Obviously the resulting time limit is a scalar, not a 
vector.  My apologies for any confusion.


                                  Scott Bennett, Comm. ASMELG, CFIAG
                                  Systems Programming
                                  Northern Illinois University
                                  DeKalb, Illinois 60115
**********************************************************************
* Internet:       bennett@cs.niu.edu                                 *
* BITNET:         A01SJB1@NIU                                        *
*--------------------------------------------------------------------*
*  "...And the heat came round and busted me                         *
*      For smilin' on a cloudy day!                                  *
*      Coming, coming, coming around..."                             *
**********************************************************************

From cellular-automata-request@Think.COM  Sun Oct 13 15:05:46 1991
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Date: 13 Oct 91 18:39:27 GMT
From: park@cs.bu.edu (Kihong Park)
Organization: Computer Science Department, Boston University, Boston, MA, USA
Subject: Re: phase transitions in CA space
Message-Id: <91535@bu.edu>
Newsgroups: comp.theory.cell-automata
References: <1991Oct3.131828.2759@nic.unh.edu>, <19911003160205.0.ACW@PALLANDO.SCRC.Symbolics.COM>
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To: ca@Think.COM

In article <19911003160205.0.ACW@PALLANDO.SCRC.Symbolics.COM> ACW@YUKON.SCRC.Symbolics.COM (Allan C. Wechsler) writes:

>My difficulty is, that since the space of rules is discrete, and the
>diagnostic measurement is surely statistical, it will never be exactly
>zero.  Each actual rule will lie on one side or other of the frontier.
>You might have to run the rule for a long time to determine which side
>of the line it was on, but it would always be on one side or the other.
>
>On the other hand, universality is a well-defined, provable property
>that some rules have and some rules don't.  There's clearly a "universal
>region" in rule space.  Langton's thesis, identifying universal automata
>with critical points on a phase-boundary, can't be right in its exact
>form.  And if the thesis is weakened, to say that universal rules lie
>"near" a transition, then we are left wondering just how near is near.

I would like to mention that universality is an undecidable property, and hence
not a "provable property" as indicated above. This implies that whatever
computable "indicator" one comes up with for classifying CAs in rule space,
the indicator must be of an approximate character. Certainly, Chris' lambda
parameter is computable, and hence of such nature.

	I don't think Chris asserts in his work that his parameter has such
prowness of deciding unsolvable problems; it is a reasonably good indicator for
guessing with high probability whether a rule is "complex" or not without
having to simulate the process.

	This doesn't mean that phase transitions in the technical sense can't be
formulated using some parameter; a noncomputable parameter may be shown to
exist w.r.t. which exact phase transitions do occur. One such candidate is the
Kolmogorov complexity or algorithmic complexity of a rule. This is a noncomputa-
ble indicator, and Chris' lambda parameter can be viewed as a first order
statistic which measures the "randomness" of a rule. 

	Briefly, I define the Kolmogorov complexity(K) of a CA rule as K(x)
where x is a binary string that encodes the rule(cf. Wolfram's standard way 
of encoding rules as integers). There are results which show that K(x) is
invariant under different orderings of the encoding(permutations of x) modulo
a very small subset.

	This is the subject of some ongoing work, and hopefully we'll be able
to write something up in the near future. In any event, the main point as I see
it in this line of approach lies in the notion that rules can be associated with
measures of "complexity" which in turn are related to the "complexity" of
the CA behavior that they give rise to.

Regards, Kihong Park
--
Computer Science Department		E-mail: park@cs.bu.edu
111 Cummington Street			Tel.:	(617) 353 - 6412 (o)
Boston University				(617) 232 - 5582 (h)
Boston, MA 02215

From cellular-automata-request@Think.COM  Sun Oct 13 16:40:34 1991
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Date: Sun, 13 Oct 91 19:58 GMT
From: Eamonn Sullivan <0004520856@mcimail.com>
To: List Server <ca@Think.COM>
Subject: add me to the list
Message-Id: <90911013195809/0004520856PK1EM@mcimail.com>

Could I please be added to the digest mailing list for this group.  My email address is 4520856@mcimail.com.



From cellular-automata-request@Think.COM  Sun Oct 13 19:05:52 1991
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Date: 13 Oct 91 21:54:53 GMT
From: 2fqqdrfs@kuhub.cc.ukans.edu
Organization: University of Kansas Academic Computing Services
Subject: Re: phase transition and univ computation
Message-Id: <1991Oct13.165453.34469@kuhub.cc.ukans.edu>
Newsgroups: comp.theory.cell-automata
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In article <9110111215.AA07687@custard.think.com>, hiebeler@Think.COM (David Hiebeler) writes:
>   The argument doesn't directly apply to fortresses, but it points out
> that you can't win a similar challenge, namely "design a moving
> object, and I will try to design something to stop it.  Can you build
> something that I cannot stop?"  All I would have to do to win is build
> the same thing you did, and point it at yours.
>
> Dave Hiebeler                  | Internet: hiebeler@think.com

What if you designed something that acts like a pool of detergent headed, say,
north?  That has the power to "break up" things in it's path?  You wouldn't
stop it with a fluid mass headed south...
( break up meaning shove out of the way w/o destroying. detergent vs. oil )

Where do I get a definition / discussion of Moore automata?
Are they generally cells that can look at their neighbor's states and
decide a new state for themselves, and which are all simulteneously "executed"?
Any limitation to the complexity of their formulae or number of states?

In life, that is, the variables in this formula are set to:
2d, square grid
2 possible states
range of neighbors = 1
calculation of new state limited to one logic expression


Is there any good general survey text on CA?

From cellular-automata-request@Think.COM  Mon Oct 14 16:01:29 1991
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Date: Mon, 14 Oct 1991 15:22-0400
From: Allan C. Wechsler <ACW@YUKON.SCRC.Symbolics.COM>
Subject: Re: phase transitions in CA space
To: park@cs.bu.edu, ca@Think.COM
In-Reply-To: <91535@bu.edu>
Message-Id: <19911014192230.4.ACW@PALLANDO.SCRC.Symbolics.COM>

    Date: Sun, 13 Oct 1991 14:39 EDT
    From: park@cs.bu.edu (Kihong Park)

    I would like to mention that universality is an undecidable property, and hence
    not a "provable property" as indicated above. This implies that whatever
    computable "indicator" one comes up with for classifying CAs in rule space,
    the indicator must be of an approximate character. Certainly, Chris' lambda
    parameter is computable, and hence of such nature.

I think I stumbled against technical nomenclature here.  By a "provable
property" I meant that /on occasion/ a rule can be unambiguously proved
universal -- for example, the game of life.  Furthermore, although
universality is undecidable in general, it is still true that every rule
is either universal or not (regardless of whether we could prove it).
So there unquestionably is a "universal region" in rule space, and we
can show some rules to be inside and some to outside this region.  Of
course, the boundary of the universal region will always be fuzzy to us
because there are rules that cannot be categorized.  (This doesn't mean
they don't belong to one of the two categories, it just means we can't
find out which.)

From cellular-automata-request@Think.COM  Mon Oct 14 22:06:28 1991
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Date: 15 Oct 91 00:30:45 GMT
From: adam@flammulated.rice.edu (Adam Thornton, Lost in the GUE)
Organization: Glider Guns ate my brain
Subject: Ants?  By Rudy Rucker, I think?
Message-Id: <1991Oct15.003045.10107@rice.edu>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM

A _looooong_ while ago here, there was a discussion of a product called "Ants",
a CA thingy that ran under MSDOS; I think it was written by Rudy Rucker.

If anyone has any information about it, could you please post or e-mail me?
Thanks.

Adam Thornton


--
Adam Thornton  |  Opinions are mine alone, though Rice is welcome to them.
 adam@{owlnet, is, ricevm1}.rice.edu | adam@ricevm1.bitnet | :-) :-) :-)
     -->Welcome to Alpha Complex!  The Computer is your Friend!<--
   "None of us will be free until nerd persecution ends."  |  64,928

From cellular-automata-request@Think.COM  Tue Oct 15 10:05:30 1991
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Date: Tue, 15 Oct 1991 13:07:09 GMT
From: scott@scotty.life.uiuc.edu (      )
Organization: University of Illinois at Urbana
Subject: Re: Ants? By Rudy Rucker, I think?
Message-Id: <scott.687532029@scotty>
Newsgroups: comp.theory.cell-automata
References: <1991Oct15.003045.10107@rice.edu>
Sender: ca-request@Think.COM
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There's a product by Maxis, for the Macintosh, called SimAnt, that does
much of the same....



--
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
|` sjhg9320@uxa.cso.uiuc.edu               Graduate Research Assistant	'|
|` scott@scotty.life.uiuc.edu              Department of Microbiology	'|
|` Scott_Howard@QMS1.life.uiuc.edu         University of Illinois	'|

From cellular-automata-request@Think.COM  Tue Oct 15 14:28:15 1991
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Date: Tue, 15 Oct 91 11:03:16 PDT
From: autodesk!air!rudy@fernwood.mpk.ca.us (Rudy Rucker)
Message-Id: <9110151803.AA00862@air.acad>
To: ca@Think.COM
Subject: Re: Ants? By Rudy Rucker, I think?


Earlier this year I sent out shareware copies of a program called
ant21.exe.  This program shows evolving two-dimensional turing machines.
Like a turing machine, each ant has an internal state and sees and
writes on only the cell (pixel) right under it.  The two-d aspect is
that instad of just moving L and R, it can move in any of a windrose
of 4,6,12,etc. directions.  Kee Dewdney wrote a column about these
critters, calling them Turmites.  Christopher Langton implemented some
of them as cellular automata, calling them Vants.  I was able to
implement some of them in CA Lab (the Autodesk cellular automata
program), and then switched to a stand-alone program, since it's not
very efficient to simulate them as a CA (for then you update each
cell with an instructions like, "if you're an ant do such and such,
otherwise stay the same).

I soon found that with multi-state ants with large windroses, it
becomes intractably difficult to figure out which lookup tables will
make cool looking or interesting ants.  So then I fixed the program
so the lookup tables evolve.  Each ant has three lookups which map
i) state & readcolor -> new state ii) state & readcolor -> direction
change and iii)state -> writecolor.  In iii) the readcolor is not
taken into account as I assume the ants always erase marked cells...
this simply because it seems to give better behavior.  

I formulated several kinds of "games" for the ants to play so that
they would have score rankings for a basis of natural selelction.
A typical set up is to have 3 colonies consisting of 5 ants each.  Ants
in the same colony leave the same color trail cells.  So there are like
5 red ants, 5 blue ants, 5 green ants.  Group them into a predation loop
so that red preys on blue which preys on green which preys on red.  If
an ant encounters a trail cell of its prey it gets +2 points.  If it
encounters a trail cell of its predator it gets -1 point.  Every 1000
cycles (say) each colony has a private colony meeting.  The three lowest
scoring ants have their lookup tables erased.  One table is randomized,
one is make a slightly mutated copy of the best ant, and one table is
a sex cross of the best two ants. Two interesting kinds of sex are
row shuffling and column shuffling.  That is either i) whenever you're
in state such and such act like your Dad, other wise like  your Mom,
or ii) whenever you see readcolor such and such act like Dad otherwise
like Mom.

They do evolve pretty interestingly.  Though evolution is still slow,
and there are many things I haven't tried yet.

If you didn't get ant21.exe and still want to see it, send a WRITTEN
request to Rudy Rucker, ANTS!, Autodesk Inc., 2320 Marinship Way,
Sausalito, CA 94965.

Quite recently I've been porting ants to Windows so that it will be
easier to design individual ants and to generate graphs and other
analyses of the runs.  My plan/hope is that this will eventually be
part of an Artificial Life Laboratory product from the Autodesk
Science Series.  Info about Autodesk Science Series products CA Lab
and CHAOS can be gotten by phoning 1-800-688-2344.  For those of
you who've seen this before, sorry to repeat the plug.

Maxis of Orinda California will ship soon (in December I think) a
product called SimAnt.  This is along the lines of their great
SimCity and SimEarth products.  SimAnt will run on the Mac and the PC.
I've seen an early version of the game, which is being written by a
hacker supreme called Will Wright.  It does not actually have much
overlap with the "ant" program I have been working on.  In SimAnt
there are two colonies of ants trying to get into a man's house, to
find food, to build colonies, etc.  The graphics are very detailed
and engrossing.  The ants are controlled by setting a farily large
panel of sliders and switches, things like "how important is food
search relative to fighting".  In this way the game is a lot like
SimCity.  The game does not include, so far as I know, any element
of evolution --- the user makes all changes in the colony himself.

It is likely that the next Maxis product after SimAnt WILL include
more true A-Life features.


From cellular-automata-request@Think.COM  Tue Oct 15 16:06:35 1991
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Date: Tue, 15 Oct 91 19:37:42 GMT
From: robertc@sco.COM (cry Kahn strobe )
Organization: The Santa Cruz Operation, Inc.
Subject: Re: phase transitions in CA space
Message-Id: <14848@scolex.sco.COM>
Newsgroups: comp.theory.cell-automata
References: <91535@bu.edu>, <19911014192230.4.ACW@PALLANDO.SCRC.Symbolics.COM>
Sender: ca-request@Think.COM
To: ca@Think.COM


In article <19911014192230.4.ACW@PALLANDO.SCRC.Symbolics.COM> ACW@YUKON.SCRC.Symbolics.COM (Allan C. Wechsler) writes:
> ...
>can show some rules to be inside and some to outside this region.  Of
>course, the boundary of the universal region will always be fuzzy to us
>because there are rules that cannot be categorized.  (This doesn't mean
>they don't belong to one of the two categories, it just means we can't
>find out which.)

Do the uncertainty principles of quantum mechanics apply to mathematical
formulae as well?

-- 
####  #       #   #    # #    # # #    #  ###   #  ##    #### # # ### ## # # ###
#   # #      # #  ##   # ##   # # ##   # #   #  # #      #    # # #   # # #   #
#   # #     #   # # #  # # #  # # # #  # #      #  ##    ##   # # ##  ##  #   #
####  #     ##### #  # # #  # # # #  # # # ###  #    #   #    # # #   # # #   #
#     #     #   # #   ## #   ## # #   ## #   #  #    #   #    # # #   # # #   #
#     ##### #   # #    # #    # # #    #  ###   #  ##    ####  #  ### # # #   #
Robert Chansky         uunet.uu.net!ucscc!sco.com!robertc, robertc@sco.com

From cellular-automata-request@Think.COM  Wed Oct 16 12:05:38 1991
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Date: 16 Oct 91 18:18:53 GMT
From: root@iremia.fr (Operator)
Organization: Universite de la Reunion, France
Subject: grad schools for cellular
Message-Id: <957@helios.iremia.fr>
Newsgroups: sci.math,comp.theory,comp.theory.cell-automata
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Path: helios!corton!mcsun!uunet!cs.utexas.edu!utgpu!watserv1!graceland.waterloo.edu!shallit
From: shallit@graceland.uwaterloo.ca (Jeffrey Shallit)
Newsgroups: sci.math,comp.theory,comp.theory.cell-automata
Subject: grad schools for cellular automata?
Message-ID: <1991Oct6.150413.17814@watserv1.waterloo.edu>
Date: 6 Oct 91 15:04:13 GMT
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Lines: 12
Originator: shallit@graceland.waterloo.edu

Since I've gotten no responses from my first query,
I'm casting my net a bit wider this time.

A friend is interesting in doing a Ph. D. on cellular
automata.  Can anyone recommend the appropriate graduate
schools in North America or Europe where cellular
automata is an active research topic?

Thanks for your help,

Jeff Shallit
shallit@graceland.waterloo.edu

From cellular-automata-request@Think.COM  Thu Oct 17 13:02:31 1991
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Date: Thu, 17 Oct 91 12:58:42 -0400
From: dlukas@park.bu.edu (David Lukas)
Message-Id: <9110171658.AA15628@park.bu.edu>
To: TheoryNet@ibm.com, ai-ed@sun.com, ailist@KL.SRI.COM, anneal@cs.ucla.edu,
        arpanet-bboards@mc.lcs.mit.edu, biomch-l@hearn.bitnet,
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        issnnet-mlist@park.bu.edu, kaiser@yorkvm1.bitnet,
        lantra-l@finhutc.bitnet, na@Cholesky.Stanford.EDU,
        neuron@hplabs.hpl.hp.com, nl-kr@cs.rochester.edu,
        optics-l@taunivm.bitnet, para-dap@irlearn.bitnet,
        parallel@hubcap.clemson.edu, parsym@sumex-aim.stanford.edu,
        philosop@yorkvm1.bitnet, physics@mc.lcs.mit.edu,
        pkaiser@yorkvm1.bitnet, psycgrad@acadvm1.uottawa.ca,
        psych@tcsvm.bitnet, self-org@mc.lcs.mit.edu, simulation@ufl.edu,
        soft-eng@mwunix.mitre.org, vision-list@ads.com,
        wiley!ai-chi@lll-lcc.llnl.gov
Subject: Graduate study in Cognitive & Neural Systems at Boston University

(please post)

         ***********************************************
         *                                             *
         *                 DEPARTMENT OF               *
         *      COGNITIVE AND NEURAL SYSTEMS (CNS)     *
         *              AT BOSTON UNIVERSITY           *
         *                                             *
         ***********************************************

                    Stephen Grossberg, Chairman

The Boston University Department of Cognitive and Neural Systems
offers comprehensive advanced training in the neural and computational
principles, mechanisms, and architectures that underly human and
animal behavior, and the application of neural network architectures
to the solution of outstanding technological problems.

Applications for Fall, 1992 admissions and financial aid are now
being accepted for both the MA and PhD degree programs.

To obtain a brochure describing the CNS Program and a set of application
materials, write or telephone:

 Department of Cognitive & Neural Systems
 Boston University
 111 Cummington Street, Room 240
 Boston, MA 02215
 (617) 353-9481

or send a mailing address to: kellyd@cns.bu.edu

Applications for admission and financial aid should be received by
the Graduate School Admissions Office no later than January 15.

Applicants are required to submit undergraduate (and, if applicable,
graduate) transcripts, three letters of recommendation, and Graduate
Record Examination (GRE) scores. The Advanced Test should be in the
candidate's area of departmental specialization. GRE scores may be
waived for MA candidates and, in exceptional cases, for PhD candidates,
but absence of these scores may decrease an applicant's chances for
admission and financial aid.

Description of the CNS Department:

The Department of Cognitive and Neural Systems (CNS) provides advanced
training and research experience for graduate students interested in the neural 
and computational principles, mechanisms, and architectures that underlie human
and animal behavior, and the application of neural network architectures to the
solution of outstanding technological problems. Students are trained in a broad
range of areas concerning cognitive and neural systems, including vision and 
image processing; speech and language understanding; adaptive pattern
recognition; cognitive information processing; self-organization; associative
learning and long-term memory; cooperative and competitive network dynamics and
short-term memory; reinforcement, motivation, and attention; adaptive
sensory-motor control and robotics; and biological rhythms; as well as the
mathematical and computational methods needed to support advanced modeling
research and applications. The CNS Department awards MA, PhD, and BA/MA degrees.

The CNS Department embodies a number of unique features. It has
developed a core curriculum that  
consists of ten interdisciplinary graduate courses each of which 
integrates the psychological, neurobiological, mathematical, and computational 
information needed to theoretically investigate fundamental issues concerning 
mind and brain processes and the applications of neural networks to technology.
Additional advanced courses, including research seminars, are also offered.
Each course is typically taught once a week in the evening to make the program
available to qualified students, including working professionals, throughout
the Boston area. Students develop a coherent area of expertise by designing a 
program that includes courses in areas such as Biology, Computer Science, 
Engineering, Mathematics, and Psychology, in addition to courses in the CNS
core curriculum.

The CNS Department prepares students for thesis research with scientists 
in one of several Boston University research centers or groups, and with 
Boston-area scientists collaborating with these centers. The unit most closely 
linked to the department is the Center for Adaptive Systems. The Center for 
Adaptive Systems is also part of the Boston Consortium for Behavioral and 
Neural Studies, a Boston-area multi-institutional Congressional Center of 
Excellence. Another multi-institutional Congressional Center of Excellence 
focused at Boston University is the Center for the Study of Rhythmic 
Processes. Other research resources include distinguished research groups in
neurophysiology, neuroanatomy, and neuropharmacology at the Medical
School and the Charles River campus; in sensory robotics, biomedical
engineering, computer and systems engineering, and neuromuscular research 
within the Engineering School; in dynamical systems within the mathematics
department; in theoretical computer science within the Computer Science
Department; and in biophysics and computational physics within the Physics
Department. 

1991 FACULTY and STAFF of CNS and CAS:

Daniel H. Bullock         Nancy Kopell       
Gail A. Carpenter         John W.L. Merrill
Michael A. Cohen          Ennio Mingolla
H. Steven Colburn         Alan Peters
Paolo Gaudiano            Adam Reeves
Stephen Grossberg         James T. Todd
Thomas G. Kincaid         Allen Waxman


From cellular-automata-request@Think.COM  Thu Oct 17 16:07:12 1991
Received: by mail.think.com; Thu, 17 Oct 91 16:07:14 -0400
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Date: Thu, 17 Oct 91 19:05:40 GMT
From: rthomson@mesa.dsd.es.com (Rich Thomson)
Organization: Design Systems Division, Evans & Sutherland, SLC, UT
Subject: Journal of Complex Systems, Volume 5, Number 4
Message-Id: <1991Oct17.190540.22995@dsd.es.com>
Newsgroups: comp.theory.cell-automata,comp.theory.dynamic-sys,comp.theory.self-org-sys,alt.fractals
Sender: ca-request@Think.COM
To: ca@Think.COM

    ``Complex Systems

     A journal devoted to the rapid publication of research on the
     science, mathematics, and engineering of systems with simple
     components but complex overall behaviour.

     Editor:	Stephen Wolfram,
		Wolfram Research, Inc., and University of Illinois''


    Volume 5, Number 4

    Chaos-based Learning........................................359
	Paul F. M. J. Verschure

    Optimization of the Architecture of Feed-forward Neural Networks
    with Hidden Layers by Unit Elimination......................371
	Anthony N. Burkitt

    On the Relationship between Complexity and Entropy for Markov
    Chains and Regular Languages................................381
	Wentian Li

    On Dynamical Properties of Neural Networks..................401
	Fernanda Botelho and Max Garzon

    Robust Quasihomegeneous Configurations in
    Coupled Map Lattices........................................415
	L. Battiston, L. Bunimovich, and R. Lima

    Period-Doublings to Chaos in a Simple Neural Network:
    An Analytical Proof.........................................425
	Xin Wang


    ``Published six times a year by:
		Complex Systems Publications, Inc.
		P.O. Box 6149
		Champaign, IL 61826
		USA

    Subscriptions: $45 (students), $75 (individuals), $250 (institutions),
	Outside North America, add $15 (surface) or $65 (air).''


    My only connection with this publication is as a satisfied subscriber.

						-- Rich
-- 
  ``Read my MIPS -- no new VAXes!!'' -- George Bush after sniffing freon
	    Disclaimer: I speak for myself, except as noted.
UUCP: ...!uunet!dsd.es.com!rthomson			Rich Thomson
Internet: rthomson@dsd.es.com	IRC: _Rich_		PEXt Programmer

From cellular-automata-request@Think.COM  Fri Oct 18 12:06:40 1991
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Date: 17 Oct 91 23:54:40 GMT
From: mrothlis@taurus.cs.nps.navy.mil
Organization: Naval Postgraduate School, Monterey CA
Subject: Modeling FSM's
Message-Id: <3123@gemini.cs.nps.navy.mil>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM

I am looking for information on modeling finite state machines.
My project entails developing a model for communicating finite state machines.
From the model, a reachability analysis is derived.
Has anyone tried to do something similiar in C or C++(I am new to C++)?
Is there an environment/language available that allows the user to 'build'
finite state machine(s) and transitions graphically(PC or Workstation)?

Any information is greatly appreciated.  Please reply via email.

Thanks a million!

+-----------------------------------------------------------------------------+
| Jim Rothlisberger                                                           |
| Naval Postgraduate School                                                   |
| Department of Computer Science   INTERNET:  mrothlis@taurus.cs.nps.navy.mil |
| SMC #1949                              OR:  7676p@cc.nps.navy.mil           |
| Monterey, CA 93943-5000            BITNET:  7676p@navpgs.bitnet             |
+-----------------------------------------------------------------------------+

From cellular-automata-request@Think.COM  Fri Oct 18 18:49:43 1991
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	id AA28763; Fri, 18 Oct 91 15:46:20 MST
Date: Fri, 18 Oct 91 15:46:18 MST
From: "Richard Schroeppel" <rcs@cs.arizona.edu>
Message-Id: <9110182246.AA04193@granjon.cs.arizona.edu>
Received: by granjon.cs.arizona.edu; Fri, 18 Oct 91 15:46:18 MST
To: ca@Think.COM, acw@yukon.scrc.symbolics.com
Subject: Will smart replicators populate a random infinite Life universe?


Allan C. Wechsler <ACW@yukon.scrc.symbolics.com> writes:

>   This counterexample is bloody brilliant, and crystallizes something that
    has been bothering me about the premise that "smarties" will eventually
    take over any randomly initialized universal CA, provided it's big
    enough.

    The point is that the Life rule itself may be volatile enough to do in
    any smarties that get fortuitously created at T=0.

    The relevant challenge is this: you have to design a configuration that
    fits inside a rectangle.  You can, of course, predict the contents of
    any inset rectangle for as far in the future as it takes light to reach
    the inset from the border.  The challenge is, to predict the contents of
    an inset rectangle farther in the future than that.  Once you have made
    your prediction, I get to put anything I want outside the outer
    rectangle, to try to violate your prediction.

    You may be able to defend yourself for a few generations, but my guess
    is that Life does not contain any really strong fortresses.

I partly disagree:  I think smarties will take over Life.

Our experience with the Life rule is that random initial
configurations churn for a few hundred to a few thousand generations,
send out a few dozen gliders, and then stabilize to a thin mixture of
mostly common objects, with an overall bit density of a few percent.

A smart replicator that was initialized by chance in an infinite random
Life universe will probably only have to contend with the ordinary junk
in its immediate neighborhood.  For this purpose, a simple shield of
random blocks, density about 1%, a few hundred cells thick, should be
sufficient.

The replicator will also have to be able to clear out the neighborhood
as preparation for reproducing.  This might be done by sending out
occasional random gliders for a long time.  The most common outcome
of a glider collision with small objects is a vanish reaction, so the
neighborhood will slowly be erased.  Lightweight SpaceShips might be
even better, since the likelihood of "return fire" is very small.
The replicator should probably sit still for a few thousand generations
after creation, to let the initial soup thin itself out.

A possibility I haven't addressed is that there are non-replicating
"berserker" configurations that grow rapidly and trash everything
in their path; something like a mil-spec version of Gosper's space-
rake.  These might be smaller than smart replicators, and hence very
much more probable, and much more common in an infinite Life Eden.
If we postulate a berserker of area 1000, a smart replicator will
still have 2^500 generations to prepare itself for the onslaught.
Simple berserkers which emit continuous glider streams (or waves)
are also vulnerable to return fire from garbage; sometimes the
garbage propagates back along the glider stream faster than the
gliders are propagating forward, and the glider generator is zapped.
The outcome here is uncertain, but I'll bet on the smarties.

In conclusion, I think that a strong fortress is not required for
smarties to ultimately take over a Life universe.

Rich Schroeppel
rcs@cs.arizona.com


From cellular-automata-request@Think.COM  Tue Oct 22 17:07:39 1991
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Date: 22 Oct 91 20:02:13 GMT
From: amhastings@ucdavis.edu (Alan Hastings)
Organization: ucdavis
Subject: 2d ca programs available by ftp
Message-Id: <10234@ucdavis.ucdavis.edu>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM

The subject says it all, almost. (Is this a FAQ? -- I'm new to this.) 
What programs implementing 2d cellular automata programs are freely available,
for Macs or SUNS (preferred).  
Given sufficent replies and/or interest I will post a summary.
Thanks.
Alan Hastings
Div. of Environmental Studies
University of California
Davis, CA
amhastings@ucdavis.edu

From cellular-automata-request@Think.COM  Tue Oct 22 21:08:01 1991
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Date: Tue, 22 Oct 1991 23:06:29 GMT
From: sands@ccu1.aukuni.ac.nz (Sands)
Organization: University of Auckland, New Zealand.
Subject: Re: 2d ca programs available by ftp
Message-Id: <1991Oct22.230629.20918@ccu1.aukuni.ac.nz>
Newsgroups: comp.theory.cell-automata
References: <10234@ucdavis.ucdavis.edu>
Sender: ca-request@Think.COM
To: ca@Think.COM

amhastings@ucdavis.edu (Alan Hastings) writes:

>The subject says it all, almost. (Is this a FAQ? -- I'm new to this.) 
>What programs implementing 2d cellular automata programs are freely available,
>for Macs or SUNS (preferred).  

Also for Ms-Dos, (or just about anything in fact!)

>Given sufficent replies and/or interest I will post a summary.

Please do.

>Thanks.
>Alan Hastings
>Div. of Environmental Studies
>University of California
>Davis, CA
>amhastings@ucdavis.edu


Greg Sands.
-----------
University of Auckland, New Zealand.

sands@esv1.aukuni.ac.nz

From cellular-automata-request@Think.COM  Wed Oct 23 02:27:41 1991
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Date: Wed, 23 Oct 91 02:25:10 -0400
From: palmer@world.std.com (Kent D Palmer)
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Subject: THINKNET  NEWSLETTER  ANNOUNCEMENT

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OCTOBER 1991                     ISSUE  001               VOLUME 1   NUMBER 1
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This is an announcement for Thinknet, an on-line magazine forum dedicated to 
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<<<<<<<<<<<<Thinknet Electronic Newsletter (c) 1991 Kent Palmer.>>>>>>>>>>>>>


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HOW TO GET YOUR COPY                                                      kdp
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From cellular-automata-request@Think.COM  Wed Oct 23 15:07:53 1991
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Date: 23 Oct 91 12:25:23 GMT
From: bessiere@imag.fr (Pierre Bessiere)
Organization: IMAG Institute, University of Grenoble, France
Subject: Equipe travaillant sur les algorithmes genetiques???
Message-Id: <27027@imag.imag.fr>
Newsgroups: imag.neuronal,fnet.combinatoire,fnet.ia,comp.theory.cell-automata,comp.theory.dynamic-sys,comp.theory.self-org-sys,comp.ai,comp.ai.neural-nets
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Bonjour a tous,

J'aimerais bien savoir quelles sont les equipes francaises et francophones
qui travaillent sur les algorithmes genetiques.

Si vous appartenez a l'une d'elles repondez moi en envoyant (si possible)
un rapide descriptif de vos activites.

Je diffuserais a tous ceux qui ont repondu une compilation des reponses
obtenues.

Merci d'avance.

PS: Nous sommes une equipe de l'IMAG de l'universite de Grenoble (France).
Nous avons developpe un algorithme genetique parallele tournant sur machine
SuperNode de Transputers. Notre algorithme marche sur des configurations
allant de 1 a 128 Transputers. Nous avons pu mettre en evidence une 
acceleration super-lineaire en fonction du nombre de processeurs (en 
multipliant le nombre de processeurs par K on divise le temps d'execution
par plus de K). Cet algorithme a ete applique avec des resultat tres
interessants aux deux applications suivantes:
	- partitionement de graphe
	- plannification de mouvement en robotique

Les articles suivants (decrivant ces deux applications)
peuvent etre obtenus par FTP sur le serveur IMAG (les instructions FTP
correpondantes sont donnees en fin de message):

			--------------

       A PARALLEL GENETIC ALGORITHM FOR THE GRAPH PARTITIONING PROBLEM

E-G. Talbi & P. Bessiere
ACM-ICS91 (International Conference on Supercomputing)
Cologne, Gremany, 1991

Genetic algorithms are stochastic search and optimization techniques 
which can be usedf for a wide range of applications. This paper 
addresses the application of genetic algorithms to the graph 
partitioning problem. Standard genetic algorithms with large 
populations suffer from lack of efficiency (quite high execution time). 
A massively parallel genetic algorithm is proposed, an implementation on 
a SuperNode( of Transputers( and results of various benchmarks are given. 

The parallel algorithm shows a superlinear speed-up, in the sense 
that when multiplying the number of processors by p, the time 
spent to reach a solution with a given score, is divided by kp (k>1). 

A comparative analysis of our approach with hill-climbing algorithms 
and simulated annealing is also presented. The experimental 
measures show that our algorithm gives better results concerning both 
the quality of the solution and the time needed to reach it.

			---------------

		USING GENETIC ALGORITHMS FOR ROBOT MOTION PLANNING
				(DRAFT, do not quote)

Submited to ACM-ICRA92 to be held in Paris, France in 1992

We present an ongoing research on robot motion planning with genetic
algorithms. Our goal is to use this technique to build fast motion
planners for robot with six or more degree of freedom. After a short review
of the existing methods, we will introduce the genetic algorithms by
showing how they can be used to solve the invers kinematic problem.
Then, a theoretical justification of the approach is presented.  In the
second part of the paper, we show that the path planning problem can
be expressed as an optimization problem and thus solved with a genetic
algorithm. We illustrate the approach by building a path planner for a
planar arm with two degree of freedom, then we demonstrate the
validity of the method by planning paths for an holonomic
mobile robot.  Finally we describe an implementation of the selected
genetic algorithm on a massively parallel machine and show that fast
planning response is made possible by using this approach.

How to get files from IMAG?
___________________________

Anonymous ftp on:
	- 129.88.32.1

mymachine>ftp 129.88.32.1
Name: anonymous
Password: yourname@youradress
ftp>cd pub/SYMPA/NNandAG
ftp>binary
ftp>get bessiere.foo.ps.Z
ftp>quit
mymachine>uncompress bessiere.foo.ps.Z

From cellular-automata-request@Think.COM  Sat Oct 26 07:12:49 1991
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Date: Fri, 25 Oct 91 16:00:41 GMT
From: dana@rucs.faculty.cs.runet.edu (Dana Eckart)
Organization: Radford University
Subject: weather/climate simulation
Message-Id: <1991Oct25.160041.14842@rucs.faculty.cs.runet.edu>
Newsgroups: comp.theory.cell-automata,sci.geo.meteorology,sci.geo.fluids
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Is anyone aware of any weather/climate models or simulations which have been 
built/performed using cellular automata?  I would also be interested in
communicating with anyone with an interest in both cellular automata and
weather/climate modeling.  

It seems to me that the notion of local interaction, which is fundamental to 
cellular automata, is also a major part of weather/climate modeling (thus
my interest in the two topics).

All pointers to models, simulations and people welcomed.

Thanks in advance....

--------------------------------------------------------------
J Dana Eckart     INTERNET: dana@rucs.faculty.cs.runet.edu
                     SNAIL: 15 Grandview Dr/Radford, VA  24141

From cellular-automata-request@Think.COM  Sat Oct 26 07:13:30 1991
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Date: 26 Oct 91 00:16:24 GMT
From: robertc@sco.COM (Bohr nectar sky )
Organization: The Santa Cruz Operation, Inc.
Subject: Genetic Algorithms
Message-Id: <15082@scolex.sco.COM>
Newsgroups: comp.theory.cell-automata
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	I am interested in genetic algorithms, and have been trying to
get the source code to Thomas Ray's Tierra program, to no avail.  Has he
vanished off the face of the earth?  Or touring Europe, most likely.

	In any case, does a summary exist of all the genetic algorithms
that other people have tried?  A coworker of mine mentioned one in particular --
a set of programs that are set to perform some task (sorting a set of
characters), and those that do well are bred together, eventually producing
a program (are they programs?  Or state tables or what?) with a decent
sort algorithm.

	I would appreciate any information about this topic.  Please post.
-- 
####  #       #   #    # #    # # #    #  ###   #  ##    #### # # ### ## # ####
#   # #      # #  ##   # ##   # # ##   # #   #  # #      #    # # #   # ## # #
#   # #     #   # # #  # # #  # # # #  # #      #  ##    ##   # # ##  ##  #  #
####  #     ##### #  # # #  # # # #  # # # ###  #    #   #    # # #   # # #  #
#     #     #   # #   ## #   ## # #   ## #   #  #    #   #    # # #   # # #  #
#     ##### #   # #    # #    # # #    #  ###   #  ##    ####  #  ### # # #  #
Robert Chansky         uunet.uu.net!ucscc!sco.com!robertc, robertc@sco.com

From cellular-automata-request@Think.COM  Sat Oct 26 10:09:39 1991
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Date: Sat, 26 Oct 1991 10:12-0400
From: Allan C. Wechsler <ACW@YUKON.SCRC.Symbolics.COM>
Subject: Genetic Algorithms
To: robertc@sco.COM, ca@Think.COM
In-Reply-To: <15082@scolex.sco.COM>
Message-Id: <19911026141201.9.ACW@PALLANDO.SCRC.Symbolics.COM>

I corresponded briefly with Ray a few months ago.  I got a lot of source
code from him, to help me reimplement Tierra in Lisp.  I got my emulator
running OK, but I must have some assumptions wrong or not have run the
thing long enough, because my world decayed into chaos pretty darn
quick.

I'm reluctant to pass on the C code without permission to do so from
Ray, so you're back where you started there.  But I'm willing to share
my Lisp with anybody who asks for it.  As far as I know, it's
completely portable Common Lisp (+ CLOS) but it's still kind of rough
and missing some pieces.

From cellular-automata-request@Think.COM  Mon Oct 28 19:08:02 1991
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Date: 28 Oct 91 23:19:47 GMT
From: ulall@pub.uwrl.usu.edu
Organization: utah water research lab, utah state u
Subject: agu special session on predictability of climate and hydrology
Message-Id: <1991Oct28.231947.7868@fcom.cc.utah.edu>
Newsgroups: comp.theory.cell-automata
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AGU SPECIAL SESSION
Spring Meeting, May 11-15, 1992 Montreal, CANADA
Predictability of climatic and hydrologic systems: Insights from nonlinear
dynamics

	Nonlinear dynamical analyses are providing new insights into the
predictability and behavior of continental-scale and global climatic and
hydrologic systems. An understanding of the deterministic factors associated
with the evolution and persistence of climatic regimes, and of the relationship
between hydrologic and climatic forcings, thresholds and their responses is now
emerging. The focus of this session is on an exposition of the main techniques
of such analyses, on key results to date, directions of research, and what we
hope to learn. Presentations related to the following topics are solicited:

(1) System identification: Given a climatic or hydrologic time series how does
one identify and reconstruct the underlying system's dynamics. Methods may
include embedding methodologies, methods for nonlinear approximation and
forecasting, and estimation of invariant probability measures. Theoretical
developments of methodology as well as applications are welcome.
(2) System characterization: Low-order dynamical models of climatic and
hydrologic systems, the rationale for such models, and key insights. 
(3) Inferences from nonlinear analyses of climatic systems: Short and long term
predictability of regional, continental and global climate. Interannual,
inter-decadal, and paleo-climatic variability. Periodic and quasi-periodic
phenomena. Causes and role of sustained oscillations. Response of the climate
system to identifiable forcings: variations in solar output, in atmospheric
composition, volcanic output, El Ni o phenomena etc.
(4) Land-surface hydrology, oceans and atmospheric interactions : feedbacks,
key factors and their role. Scale issues and key variables that determine
system behavior at relevant scales. Multi-modality of the climatic signal:
identification of persistent regimes.
(5) Inferences from nonlinear analyses of hydrologic systems: Nonlinearity of
large scale hydrology: the role of heterogeneity, of boundary conditions and
climatic forcing. Surface hydrologic systems as forced oscillators:
modification of the climatic signal. Appropriate state variables for studying
large scale hydrology. Inferences on long term hydrologic variability from the
dynamics of closed basin lakes. Threshold models of streamflow generation
coupled to climatic variability. Scale issues and parametrization of hydrologic
systems: strategies for averaging in heterogeneous, nonlinear systems.
Hysteresis and chaotic behavior in coupled surface-groundwater-atmospheric
models.

Conveners: Upmanu Lall, Utah Water Research Laboratory, Utah State University,
Logan UT 84322-8200, (801)-750-3184, FAX (801)-750-3663, e-mail:
ulall@pub.uwrl.usu.edu; Michael Ghil, Dept of Atmospheric Sciences, UCLA, Los
Angeles, CA 90024-1565, (213)-825-1954, e-mail: ghil@tuolumne.atmos.ucla.edu.
Please address all correspondence to U. Lall.


Upmanu Lall											801-750-3184
Utah Water Research Laboratory						FAX 801-750-3663
Utah State University 									ulall@pub.uwrl.usu.edu
Logan UT 84322-8200

From cellular-automata-request@Think.COM  Tue Oct 29 13:41:26 1991
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From: dlukas@PARK.BU.EDU (David Lukas)
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To: TheoryNet@ibm.com, ai-ed@sun.com, ailist@KL.SRI.COM, anneal@cs.ucla.edu,
        arpanet-bboards@mc.lcs.mit.edu, biomch-l@hearn.bitnet,
        biotech@umdc.umd.edu, cellular-automata@Think.COM,
        connectionists@RI.CMU.EDU, crtnet@psuvm.bitnet,
        cybsys-l@bingvmb.bitnet, dasp-l@csearn.bitnet, denny@tss.com,
        dynsys-l@uncvm1.bitnet, ectl@snowhite.cis.uoguelph.ca,
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        optics-l@taunivm.bitnet, para-dap@irlearn.bitnet, psyc@pucc.bitnet,
        psycgrad@acadvm1.uottawa.ca, simulation@ufl.edu,
        soft-eng@mwunix.mitre.org, vision-list@ads.com
Subject: Faculty position in Cognitive & Neural Systems at Boston University


                       Assistant Professor 

                   Cognitive and Neural Systems 

                        Boston University 



Boston University seeks to hire a tenure track assistant professor 

starting in Fall 1992 for its graduate Department of Cognitive and 

Neural Systems. The Department offers an integrated curriculum 

offering the full range of psychological, neurobiological, and 

computational concepts, models, and methods in the fields 

of neural networks, computational neuroscience, parallel distributed 

processing, and biological information processing, in which Boston 

University is a leader. Candidates should have extensive analytic 

or computational research experience in modelling nonlinear neural

networks, especially in one or more of the areas: learning, speech

and language processing, adaptive pattern recognition, cognitive

information processing, and adaptive sensory-motor control. Send a 

complete curriculum vitae and three letters of recommendation to

Stephen Grossberg, Chairman, Search Committee, Department of Cognitive 

and Neural Systems, Room 240, 111 Cummington Street, Boston University, 

Boston, MA  02215, no later than January 1, 1992. Boston University 

is an Equal Opportunity/Affirmative Action employer.



If you have questions or require further information, please reply
to Carol Jefferson---caroly@cns.bu.edu.



From cellular-automata-request@Think.COM  Wed Oct 30 02:51:28 1991
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To: cellular-automata@Think.COM
From: maniezzo@ipmel2.elet.polimi.it (Vittorio Maniezzo)
Subject: query for references
Cc: maniezzo@ipmel2.elet.polimi.it

I have been asked to write a review of CAs (real-world) applications to
simulation. At the moment I am only aware of simulation of fluid dynamics.
I would welcome indications about recent articles; I can then forward what
I receive (provided I do receive something) to anybody interested.

Thanks,
   vittorio          maniezzo@ipmel2.elet.polimi.it




Vittorio Maniezzo
Dipartimento di Elettronica - Politecnico di Milano
Piazza Leonardo da Vinci 32
20133 Milano - Italy
Tel.  +39-2-2399-3622
Fax. +39-2-2399-3411
e-mail:  maniezzo@ipmel2.elet.polimi.it


From cellular-automata-request@Think.COM  Wed Oct 30 10:58:55 1991
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From: Patrick Tufts <zippy@filbert.cs.brandeis.edu>
Message-Id: <9110301601.AA12518@filbert.cs.brandeis.edu>
To: cellular-automata@Think.COM
Subject: request - pls add me to mailing list

Please add me to the cellular automata mailing list.  Thanks.

--Pat

From cellular-automata-request@Think.COM  Wed Oct 30 16:44:45 1991
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Date: 30 Oct 91 16:48:31 GMT
From: ray@brahms.udel.edu (Thomas Ray)
Organization: University of Delaware
Subject: Evolving Machine Code: Tierra Source Release
Message-Id: <25420@brahms.udel.edu>
Newsgroups: comp.theory,comp.theory.cell-automata,comp.theory.dynamic-sys,comp.theory.self-org-sys
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                             TIERRA UPDATE:
      (Source release, abstract, publications, lectures, new results)

This message contains:

1) Announcement of release of Tierra source code
2) Abstract describing Tierra
3) List of related publications and upcoming lectures
4) Some interesting new and unpublished results

1) Announcement of release of Tierra source code

     We are releasing the source now, although it is under rapid development
and major improvements are only days away.  If you use the software, be sure
to pick up new versions soon from the ftp site.  The source in the ftp site
will be replace on a roughly weekly basis.

     The complete source code for the Tierra simulator is
available by anonymous ftp at:

tierra.slhs.udel.edu [128.175.41.34] and
  life.slhs.udel.edu [128.175.41.33]

in the directory /tierra.

to get it, ftp to tierra or life, log in as user "anonymous" and give your
real name (eg. tom@udel.edu) as a password.

then give the command `cd tierra', to get a list of files type `dir'.

you will see the following files:

README.T1		A detailed description of tierra and how to use it.
README.T2		    in two parts
Part01			the source code in shar format
 ...			    in seven parts
Part07
announce    		this announcement
tierra1.tex		Parts 1 & 2 of a manuscript describing Tierra,
tierra2.tex		    in LaTeX format.

The shar files contain the README files, so if you want the source code,
you don't need to copy README separately.  To unpack the shar files, use
`unshar', or `sh'.

     The version released includes significant contributions from
Tom Uffner, Dan Pirone and Marc Cygnus.  The software remains copyrighted
("all rights reserved"), and is not being placed in the public domain.
However, it will be made available free of charge and may be freely
distributed.  The intent is that it not be used for profit making activities
unless some royalty arrangement is entered into with the authors.

     A DOS version of the Tierra software with a decent frontend will be ready
for sale ($70) by November.

2) Abstract describing Tierra

**** BEGIN ABSTRACT ****

Synthetic organisms have been created based on a computer metaphor of
organic life in which CPU time is the ``energy'' resource and memory is
the ``material'' resource.  Memory is organized into informational
patterns that exploit CPU time for self-replication.  Mutation generates
new forms, and evolution proceeds by natural selection as different
genotypes compete for CPU time and memory space.

Observation of nature shows that evolution by natural selection is
capable of both optimization and creativity.  Artificial models of evolution
have demonstrated the optimizing ability of evolution, as exemplified by
the field of genetic algorithms.  The creative aspects of evolution have been
more elusive to model.  The difficulty derives in part from a tendency of
models to specify the meaning of the ``genome'' of the evolving entities,
precluding new meanings from emerging.  I will present a natural model of
evolution demonstrating both optimization and creativity, in which the
genome consists of sequences of executable machine code.

From a single rudimentary ancestral ``creature'',
very quickly there evolve parasites, which are not able to replicate in
isolation because they lack a large portion of the genome.  However, these
parasites search for the missing information, and if they locate it in a
nearby creature, parasitize the information from the neighboring genome,
thereby effecting their own replication.

In some runs, hosts evolve immunity to attack by parasites.
When immune hosts appear, they often increase in frequency, devastating the
parasite populations.  In some runs where the community comes to be
dominated by immune hosts, parasites evolve that are resistant to immunity.

Hosts sometimes evolve a response to parasites that goes beyond immunity,
to actual (facultative) hyper-parasitism.  The hyper-parasite deceives the
parasite causing the parasite to devote its energetic resources to replication
of the hyper-parastie genome.  This drives the parasites to extinction.

Evolving in the absence of parasites, hyper-parasites completely dominate
the community, resulting in a relatively uniform community characterize by
a high degree of relationship between individuals.  Under these circumstances,
sociality evolves, in the form of creatures which can only replicate in
aggregations.

The cooperative behavior of the social hyper-parasites makes them vulnerable
to a new class of parasites.  These cheaters, hyper-hyper-parasites, insert
themselves between cooperating social individuals, deceiving the social
creatures, causing them to replicate the genomes of the cheaters.

The only genetic change imposed on the simulator is
random bit flips in the machine code of the creatures.  However, it turns
out that parasites are very sloppy replicators.  They cause significant
recombination and rearrangement of the genomes.  This spontaneous sexuality
is a powerful force for evolutionary change in the system.

One of the most interesting aspects of this instance of life is
that the bulk of the evolution is based on adaptation to the biotic
environment rather than the physical environment.  It is co-evolution
that drives the system.

**** END ABSTRACT ****

3) List of related publications and upcoming lectures

    The recent publicity about my work (Technology Review, April 1991;
Science News, August 10, 1991; New York Times, August 27, 1991; Computerworld
September 30, 1991) has generated a lot of interest.  I wanted to list the
relevant publications, and also the upcoming seminars.

Ray, T. S.  1991.  ``Is it alive, or is it GA?''
Proceedings of the 1991 International Conference on Genetic Algorithms,
Eds. Belew, R. K., and L. B. Booker, San Mateo, CA: Morgan Kaufmann, 527--534.

Ray, T. S.  1991.  ``An approach to the synthesis of life.''
Artificial Life II, Santa Fe Institute Studies in the Sciences of
Complexity, vol. XI, Eds. C. Langton, C. Taylor, J. D. Farmer, & S. Rasmussen,
Redwood City, CA: Addison-Wesley, 371--408.

Ray, T. S.  1991.  ``Population dynamics of digital organisms.''
Artificial Life II Video Proceedings,  Ed. C. G. Langton,
Redwood City, CA: Addison Wesley.

Ray, T. S.  1991.  ``Evolution and optimization of digital organisms.''
Scientific Excellence in Supercomputing: The IBM 1990 Contest Prize Papers,
Eds. Keith R. Billingsley, Ed Derohanes, Hilton Brown, III.
Athens, GA, 30602, The Baldwin Press, The University of Georgia.
Publication date: December 1991.

I will be at the Santa Fe Institute Feb. 1 thru Aug. 31, 1992.
This work will also be presented in the following upcoming seminars:

University of Maryland, Zoology, October 29, 1991
University of Kentucky, Lexington, Biology, October 31, 1991
University of Delaware, Entomology, November 5, 1991
Stony Brook, Department of Ecology and Evolution, November 6, 1991
Drexel University, Electrical Engineering, November 8, 1991
The University of the Arts, Philadelphia, Design in Cyberspace lectures,
     November 12, 1991
IBM, T. J. Watson Research Center, Yorktown Heights, NY, November 13, 1991
Thinking Machines Corp., Cambridge, November 14, 1991
Digital Equipment Corp., Hudson, MA, November 15, 1991
American Society of Information Science, New Jersey, November 19, 1991
Texas Instruments, Dallas, November 21, 1991
Harvard University, Biology (Lewontin's lab), December 2, 1991
Boston University, Computational Sciences Center, December 3, 1991
MIT Nanotechnology Study Group, December 3, 1991
University of Massachusetts Boston, Biology, December 5, 1991
Yale University, Biology, December 6, 1991
University of Arizona, Ecology & Evolutionary Biology, March 10, 1992
Cornell University, Mathematical Sciences Institute, CA Workshop, May 1992
Gordon Conference on Theoretical Biology, New Hampshire, June 8--12, 1992

4) Some interesting new and unpublished results

Below is a report of an interesting result that is not described in
any of the publications listed above:

A COMPLEX ADAPTATION

The adaptation described below is a classic example of intricate design in
evolution.  One wonders how it could have arisen through random bit flips,
as every component of the code must be in place in order for the algorithm
to function.  Yet the code includes a classic mix of apparent intelligent
design, and the chaotic hand of evolution.  The optimization technique is a
very clever one invented by humans, yet it is implemented in a mixed up but
functional style that no human would use (unless perhaps very intoxicated).

The arms race described in the manuscripts took place over a period of
a billion instructions executed by the system.  Another run was allowed to
continue for fifteen billion instructions, but was not examined in detail.
A creature present at the end of the run was examined and found to have
evolved an intricate adaptation.  The adaptation is an optimization technique
known as ``unrolling the loop''.

The central loop of the copy procedure performs the following operations:
1) copies an instruction from the mother to the daughter, 2) decrements the
cx register which initially contains the size of the parent genome, 3) tests
to see if cx is equal to zero, if so it exits the loop, if not it remains
in the loop, 4) increments the ax register which contains the address in the
daughter where the next instruction will be copied to, 5) increments the
bx register which contains the address in the mother where the next instruction
will be copied from, 6) jumps back to the top of the loop.

The work of the loop is contained in steps 1, 2, 4 and 5.  Steps 3 and 6 are
overhead.  The efficiency of the loop can be increased by duplicating the
work steps within the loop, thereby saving on overhead.  The creature from
the end of the long run had repeated the work steps three times within the
loop, as illustrated below.

The unrolled loop is an example of the ability of evolution to produce an
increase in complexity, gradually over a long period of time.  The interesting
thing about the loop unrolling optimization technique is that it requires more
complex code.  The resulting creature has a genome size of 36, compared to its
ancestor of size 80, yet it has packed a much more complex algorithm into less
than half the space.

Below I include the assembler code for the central copy loop of the ancestor
(80aaa) and decendant after fifteen billion instructions (72etq).  Within
the loop, the ancestor does each of the following operations once: copy
instruction (51), decrement cx (52), increment ax (59) and increment bx (60).
The decendant performs each of the following operations three times within
the loop: copy instruction (15, 22, 26), increment ax (20, 24, 31) and
increment bx (21, 25, 32).  The decrement cx operation occurs five times
within the loop (16, 17, 19, 23, 27).  Instruction 28 flips the low order
bit of the cx register.  Whenever this latter instruction is reached, the
value of the low order bit is one, so this amounts to a sixth instance of
decrement cx.  This means that there are two decrements for every increment.

The reason for this is related to another adaptation of this creature.  When
it calculates its size, it shifts left (12) before allocating space for the
daughter (13).  This has the effect of allocating twice as much space as
is actually needed to accomodate the genome.  The genome of the creature
is 36 instructions long, but it allocates a space of 72 instructions.
This occurred in an environment where the slice size was set equal to the
size of the cell.  In this way the creatures were able to garner twice as
much energy.  However, they had to compliment this change by doubling the
number of decrements in the loop.

nop_1    ; 01  47 copy loop template      COPY LOOP OF 80AAA
nop_0    ; 00  48 copy loop template
nop_1    ; 01  49 copy loop template
nop_0    ; 00  50 copy loop template
mov_iab  ; 1a  51 move contents of [bx] to [ax] (copy instruction)
dec_c    ; 0a  52 decrement cx
if_cz    ; 05  53 if cx = 0 perform next instruction, otherwise skip it
jmp      ; 14  54 jump to template below (copy procedure exit)
nop_0    ; 00  55 copy procedure exit compliment
nop_1    ; 01  56 copy procedure exit compliment
nop_0    ; 00  57 copy procedure exit compliment
nop_0    ; 00  58 copy procedure exit compliment
inc_a    ; 08  59 increment ax (point to next instruction of daughter)
inc_b    ; 09  60 increment bx (point to next instruction of mother)
jmp      ; 14  61 jump to template below (copy loop)
nop_0    ; 00  62 copy loop compliment
nop_1    ; 01  63 copy loop compliment
nop_0    ; 00  64 copy loop compliment
nop_1    ; 01  65 copy loop compliment (10 instructions executed per loop)


shl     ; 000 03  12 shift left cx        COPY LOOP OF 72ETQ
mal     ; 000 1e  13 allocate daughter cell
nop_0   ; 000 00  14 top of loop
mov_iab ; 000 1a  15 copy instruction
dec_c   ; 000 0a  16 decrement cx
dec_c   ; 000 0a  17 decrement cx
jmpb    ; 000 15  18 junk
dec_c   ; 000 0a  19 decrement cx
inc_a   ; 000 08  20 increment ax
inc_b   ; 000 09  21 increment bx
mov_iab ; 000 1a  22 copy instruction
dec_c   ; 000 0a  23 decrement cx
inc_a   ; 000 08  24 increment ax
inc_b   ; 000 09  25 increment bx
mov_iab ; 000 1a  26 copy instruction
dec_c   ; 000 0a  27 decrement cx
or1     ; 000 02  28 flip low order bit of cx
if_cz   ; 000 05  29 if cx == 0 do next instruction
ret     ; 000 17  30 exit loop
inc_a   ; 000 08  31 increment ax
inc_b   ; 000 09  32 increment bx
jmpb    ; 000 15  33 go to top of loop (6 instructions per copy)
nop_1   ; 000 01  34 bottom of loop    (18 instructions executed per loop)

                             Tom Ray
                       University of Delaware
                  School of Life & Health Sciences
                      Newark, Delaware  19716
                      ray@tierra.slhs.udel.edu
                       ray@life.slhs.udel.edu
                        ray@brahms.udel.edu
                         302-451-2281 (FAX)
                            302-451-2753

From cellular-automata-request@Think.COM  Sat Nov  2 08:44:28 1991
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Date: 2 Nov 91 04:03:14 GMT
From: x409@cutmcvax.cs.curtin.edu.au (Ross Maloney)
Organization: Curtin University of Technology, Computing Science
Subject: Request for list of CA simulation source codes
Message-Id: <x409.689054594@cutmcvax>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM


I recall sometime ago there was mentioned on comp.theory.cell-automata
that a general CA simulation code was available for access via FTP.
I thought that the code had been submitted to one of the source
news groups such as comp.sources.x, comp.sources.misc, etc.  However,
the only one I could find there was xlife - interesting, but by no means
general.  Could someone clear up my confused memory and maybe, post
a list of such codes and from where they are available.

Thanks.
=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=
Ross Maloney                         =  voice:  (home) +61 9 364 1927
                                     +          (work) +61 9 420 3106
Graduate Student                     =
School of Computing Science          +
Curtin University of Technology      =  email:  x409@cutmcvax.cs.curtin.edu.au
Perth, WA.                           +
AUSTRALIA                            =
=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=

From cellular-automata-request@Think.COM  Sun Nov  3 11:43:05 1991
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Date: 3 Nov 91 16:03:46 GMT
From: jesjones@milton.u.washington.edu (Jesse Jones)
Organization: University of Washington, Seattle
Subject: Cellular Automata program for Macs
Message-Id: <1991Nov3.160346.12848@milton.u.washington.edu>
Newsgroups: comp.theory.cell-automata
References: <x409.689054594@cutmcvax>
Sender: ca-request@Think.COM
To: ca@Think.COM

A while back someone posted an article asking about CA programs for
Macs. I should have replied then but I'm brand new to Usenet so I
didn't. I wrote a program called LifeMaker last summer. The latest
version is 2.0 (which added the rule editor). The program has been
uploaded to CompuServe, BIX, and probably other places. LifeMakers
features include:

1) Three different neighborhoods: five neighbors, nine neighbors, and
the Margolus space. Each cell has four states. Each state has a user
defined color.

2) The cell space is displayed in a standard Mac window complete with
scroll bars and a zoom box. You can zoom in or out and the number of
cells can be changed.

3) A small language is included so people with a bit of programming
experience can write their own rules. There are about 30 rules built in.

4) There is a Pattern menu associated with each rule for saving neat
patterns. New patterns can be added and old patterns deleted.

5) There's a tool window for drawing. It includes stuff like: a
selection tool (for dragging, cut/paste etc.), an eraser, a pencil,
a paint bucket, a line tool, and tools to draw circles and rectangles 
(both filled and outlines).

6) There's also an edit menu that includes things like rotate, flip,
random, and invert.

  --Jesse

From cellular-automata-request@Think.COM  Mon Nov  4 05:43:38 1991
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Date: 1 Nov 91 14:38:40 GMT
From: gupta@prlhp1.prl.philips.co.uk (Ashok Gupta)
Organization: Philips Research Laboratories, Redhill, UK
Subject: CFP - Cellular Automata
Message-Id: <1461@prlhp1.prl.philips.co.uk>
Newsgroups: comp.theory.cell-automata,comp.theory,comp.theory.self-org-sys,comp.theory.dynamic-sys,comp.ai,sci.physics
Sender: ca-request@Think.COM
To: ca@Think.COM


                          The British Computer Society 
                       Parallel Processing Specialist Group

                                    Second
                               Call For Papers
                               
                               One day Meeting
                                      On

                              CELLULAR  AUTOMATA

                                  Feb 12 1992
                               Imperial College
                                  London, U.K.


 o  Special Purpose Hardware for Cellular Automata

 o  Cellular Automata Simulation on other architectures

 o  Software Systems for Cellular Automata

 o  Use of Cellular Automata models to simulate systems in the physical
      and biological sciences

 o  Visualisation of Cellular Models


Provisional List Of Speakers :-

    G.S. Pawley   Univ of Edinburgh
    R. Taylor     Univ of York
    F. George     Univ of Edinburgh
    B. Martin     Univ of Lyon, France
    A. Broggi     Parma, Italy


If you wish to contribute please send a brief abstract to :-

    Prof. Dennis Parkinson
    A.M.T.
    65 Suttons Park Avenue
    Reading
    U.K.
    RG6 1AZ
    Telephone: +44 734 661111     Electronic Mail :-  dp@amthq.co.uk

From cellular-automata-request@Think.COM  Mon Nov  4 10:43:14 1991
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Date: 4 Nov 91 14:33:11 GMT
From: butterwo@copland.cs.unc.edu (Jeff Butterworth)
Subject: Enhanced HPP LGA Model
Message-Id: <7314@borg.cs.unc.edu>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM


Maybe this article never got out of our site, because I never received any
responses.  If you read this, then could you please at least send me some
e-mail to verify that I'm posting correctly?  Thanks!

-------------------------------------------------------------------------------

I recently read a LGA (lattice gas automata) paper that explains an
interesting way of achieving isotropy in 2D.  This method modifies a
rectangular lattice (like HHP) rather than using a triangular one (like FHP).

The paper is "Lattice Gas Models for 3D Hydrodynamics" by D'Humeires,
Lallemand, and Frisch in Europhysics Letters, 2(4), pp. 291-297 (1986).

The basic change is that diagonal connections are made between each site
and it's second nearest neighbors.  Particles moving along these diagonal
paths must still get to the next site in one time step, so they move at
sqrt(2) times the speed of the vertical and horizontal particles.
One might ask how these faster particles can collide with slower particles
and still conserve mass and momentum.  To do this, stationary particles
are also introduced.  An example collision involving all three speeds
is shown below.

Here we see two speed 1 particles approaching a site from the west and south.
After the collision, one particle moves northeast and the other stops.
Mass, momentum, and energy are conserved.

p == particle
* == site

before		movement	collision
		phase		phase
	  
 *  *  *         *  *  *          *  *  *
        
	            p 		      p
 *p *  *         *  *p *          *  p  *
	                                 
    p  
 *  *  *         *  *  *          *  *  *

The "graphics" above show nine sites of a lattice.  Each particle is shown
next to the lattice site at which it is stored.  The direction of movement
of a particle is determined by drawing a vector from the site to the particle.

The fact that this lattice is rectangular makes the implementation simpler
than FHP for some computers.  Does anyone have an opinion about whether
this method will work better, as well, or worse than FHP?  Does anyone think
that this method still doesn't give isotropy?  Unfortunately, I don't
know anything about group theory so I'm not qualified to answer these
questions.


Jeff Butterworth

Home: 100-H Misty Woods Circle, Chapel Hill, NC 27514 (919) 967-7359
School: 342 Sitterson, UNC-Chapel Hill, NC 27599 (919) 962-1849
E-Mail:	butterwo@cs.unc.edu

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Message-Id: <9111061458.AA17643@fenway.bu.edu>
To: TheoryNet@ibm.com, ai-ed@sun.com, ailist@KL.SRI.COM, anneal@cs.ucla.edu,
        arpanet-bboards@mc.lcs.mit.edu, biomch-l@hearn.bitnet,
        biotech@umdc.umd.edu, cellular-automata@Think.COM,
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        dynsys-l@uncvm1.bitnet, ectl@snowhite.cis.uoguelph.ca,
        human-nets@aramis.rutgers.edu, hypercube@hubcap.clemson.edu,
        ieee-l@bingvmb.cc.binghamton.edu, image-l@trearn.bitnet,
        info-futures@encore.com, ir-l%uccvma.bitnet@vm1.nodak.edu,
        issnnet-mlist@PARK.BU.EDU, lantra-l@finhutc.bitnet,
        na@Cholesky.Stanford.EDU, neuron@hplabs.hpl.hp.com,
        nl-kr@cs.rochester.edu, optics-l@taunivm.bitnet,
        para-dap@irlearn.bitnet, psyc@pucc.bitnet, psycgrad@acadvm1.uottawa.ca,
        simulation@ufl.edu, soft-eng@mwunix.mitre.org, vision-list@ads.com
Subject: Courses and Conference on Neural Networks, May 1992, Boston University


                          BOSTON UNIVERSITY 

                            NEURAL NETWORK
                        COURSES AND CONFERENCE

               COURSE 1: INTRODUCTION AND FOUNDATIONS
                          May 9 - 12, 1992
         A systematic introductory course on neural networks.

                 COURSE 2: RESEARCH AND APPLICATIONS
                          May 12 - 14, 1992
        Eight tutorials on current research and applications.

                  CONFERENCE: NEURAL NETWORKS FOR 
                 LEARNING, RECOGNITION, AND CONTROL
                         MAY 14 - 16, 1992

    An international research conference presenting INVITED and
                        CONTRIBUTED papers.

          Sponsored by Boston University's Wang Institute,
                 Center for Adaptive Systems, and 
                   Department of Cognitive and Neural Systems, 
                  with partial support from the 
             Air Force Office of Scientific Research.  

NEURAL NETWORK COURSES
May 9 - 14, 1992

This self-contained, systematic, five-day course is based on the
graduate curriculum in the technology, computation, mathematics, and
biology of neural networks developed at the Center for Adaptive
Systems (CAS) and the Department of Cognitive and Neural Systems
(CNS) at Boston University.  This year's curriculum refines and
updates the successful course held at the Wang Institute of Boston
University in May 1990 and 1991.  A new two-course format permits
both beginners and researchers to participate.  The course
will be taught by CAS/CNS faculty, as well as by distinguished guest
lecturers at the beautiful and superbly equipped campus of the Wang
Institute.  An extraordinary range and depth of models, methods, and
applications will be presented.  Interaction with the lecturers and
other participants will continue at the daily discussion sessions,
meals, receptions, and coffee breaks that are included with
registration.  At the 1990 and 1991 courses, participants came from
many countries and from all parts of the United States.  

Course Faculty from Boston University are Stephen Grossberg, Gail
Carpenter, Ennio Mingolla, and Daniel Bullock.  Course guest
lecturers are John Daugman, Federico Faggin, Michael I. Jordan, Eric
Schwartz, Alex Waibel, and Allen Waxman.  

COURSE 1 SCHEDULE
SATURDAY, MAY 9, 1992

4:00 - 6:00 P.M. Registration 
5:00 - 7:00 P.M. Reception

SUNDAY, MAY 10, 1992

Professor Grossberg: Historical Overview, Cooperation and 	   
Competition, Content Addressable Memory, and Associative Learning. 
Professors Carpenter and Mingolla: Neocognitron, Perceptrons, and   
   Introduction to Back Propagation. 
Professor Grossberg and Mingolla: Adaptive Pattern Recognition.  

MONDAY, MAY 11, 1992

Professor Grossberg: Introduction to Adaptive Resonance Theory. 
Professor Carpenter: ART 1, ART 2, and ART 3. 
Professors Grossberg and Mingolla: Vision and Image Processing.  
Professors Bullock and Grossberg: Adaptive Sensory-Motor Control and
	Robotics

TUESDAY, MAY 12, 1992

Professor Bullock and Grossberg: Adaptive Sensory-Motor Control and
	Robotics, continued.  
Professor Grossberg: Speech Perception and Production, Reinforcement
	Learning and Prediction. 

End of Course 1 (12:30 P.M.)


COURSE 2 SCHEDULE


TUESDAY, MAY 12, 1992
11:30 A.M. - 1:30 P.M. Registration

Professor Carpenter: Fuzzy Artmap. 
Dr. Waxman: Learning 3-D Objects from Temporal Sequences. 

WEDNESDAY, MAY 13, 1992

Professor Jordan: Recent Developments in Supervised Learning.  
Professor Waibel: Speech Recognition and Understanding.  
Professor Grossberg: Vision, Space, and Action. 
Professor Daugman: Signal Processing in Neural Networks.  

THURSDAY, MAY 14, 1992

Professor Schwartz: Active Vision.  
Dr. Faggin: Practical Implementation of Neural Networks.

End of Course 2 (12:30 P.M.)

                       RESEARCH CONFERENCE

      NEURAL NETWORKS FOR LEARNING, RECOGNITION, AND CONTROL

                         MAY 14-16, 1992

This international research conference on topics of fundamental
importance in science and technology will bring together leading
experts from universities, government, and industry to present their
results on learning, recognition, and control, in invited lectures
and contributed posters.  Topics range from cognitive science and
neurobiology through computational modeling to technological
applications.  

CALL FOR PAPERS:  A featured poster session on neural network
research related to learning, recognition, and control will be held
on May 15, 1992.  Attendees who wish to present a poster should
submit three copies of an abstract (one single-spaced page),
postmarked by March 1, 1992, for refereeing.  Include a cover letter
giving the name, address, and telephone number of the corresponding
author.  Mail to: Poster Session, Neural Networks Conference, Wang
Institute of Boston University, 72 Tyng Road, Tyngsboro, MA 01879. 
Authors will be informed of abstract acceptance by March 31, 1992. 
A book of lecture and poster abstracts will be given to attendees at
the conference.  

CONFERENCE PROGRAM

THURSDAY, MAY 14, 1992
2:00 P.M. - 5:00 P.M. Registration
3:00 P.M. - 5:00 P.M. Reception

Professor Richard Shiffrin, Indiana University: "The Relationship
	between Composition/Distribution and Forgetting"
Professor Roger Ratcliff, Northwestern University: "Evaluating 
   Memory Models"
Professor David Rumelhart, Stanford University: "Learning and
   Generalization in a Connectionist Network" 

FRIDAY, MAY 15, 1992

Dr. Mortimer Mishkin, National Institute of Mental Health: "Two 
   Cerebral Memory Systems"
Professor Larry Squire, University of California, San Diego: "Brain
   Systems and the Structure of Memory"  
Professor Stephen Grossberg, Boston University, "Neural Dynamics of
   Adaptively Timed Learning and Memory"
Professor Theodore Berger, University of Pittsburgh: "A Biological
	Neural Model for Learning and Memory" 
Professor Mark Bear, Brown University: "Mechanisms for Experience-
	Dependent Modification of Visual Cortex"
Professor Gail Carpenter, Boston University: "Supervised Learning by
	Adaptive Resonance Networks"
Dr. Allen Waxman, MIT Lincoln Laboratory: "Neural Networks for 
   Mobile Robot Visual Navigation and Conditioning"
Dr. Thomas Caudell, Boeing Company: "The Industrial Application of
	Neural Networks to Information Retrieval and Object Recognition 
   at the Boeing Company"

POSTER SESSION (Three hours)  

SATURDAY, MAY 16, 1992  

Professor George Cybenko, University of Illinois: "The Impact of 
   Memory Technology on Neurocomputing"  
Professor Eduardo Sontag, Rutgers University: "Some Mathematical 
   Results on Feedforward Nets: Recognition and Control"  
Professor Roger Brockett, Harvard University: "A General Framework 
   for Learning via Steepest Descent"
Professor Barry Peterson, Northwestern University Medical School: 
	"Approaches to Modeling a Plastic Vestibulo-ocular Reflex"  
Professor Daniel Bullock, Boston University: "Spino-Cerebellar
	Cooperation for Skilled Movement Execution"  
Dr. James Albus, National Institute of Standards and Technology: "A
	System Architecture for Learning, Recognition, and Control"
Professor Kumpati Narendra, Yale University: "Adaptive Control of
	Nonlinear Systems Using Neural Networks"
Dr. Robert Pap, Accurate Automation Company: "Neural Network Control
	 of the NASA Space Shuttle Robot Arm"  

Discussion

End of Research Conference (5:30 P.M.)


HOW TO REGISTER:

...To register by telephone, call (508) 649-9731 (x 255)
	with VISA or Mastercard between 8:00-5:00 PM (EST).  
...To register by fax, complete and fax back the Registration Form
	to (508) 649-6926. 
...To register by mail, complete the registration form below and   
   mail it with your payment as directed.   

ON-SITE REGISTRATION:  Those who wish to register for the courses
and the research conference on-site may do so on a space-available
basis.  

SITE: The Wang Institute of Boston University possesses excellent
conference facilities in a beautiful 220-acre setting.  It is easily
reached from Boston's Logan Airport and Route 128.  

REGISTRATION FORM:  NEURAL NETWORKS COURSES AND CONFERENCE
MAY 9-16, 1992

Name: ______________________________________________________________

Title: _____________________________________________________________

Organization: ______________________________________________________

Address: ___________________________________________________________

City: ____________________________ State: __________ Zip: __________

Country: ___________________________________________________________

Telephone: _______________________ FAX: ____________________________


                    Regular Attendee        Full-time Student       

Course 1            (  ) $650                       N/A

Course 2            (  ) $650                       N/A          

Courses 1 and 2     (  ) $985                    (  )$275*

Conference          (  ) $110                    (  ) $75*

* Limited number of spaces.  Student registrations must be received
by April 15, 1992.  


Total payment:______________________________________________________

Form of payment:

	( ) Check or money order (payable in U.S. dollars to Boston
   	 University).
	( ) VISA 		( ) Mastercard

       #_________________________________Exp.Date:__________________


       Signature (as it appears on card): __________________________

Return to: Neural Networks
           Wang Institute of Boston University 
           72 Tyng Road 
           Tyngsboro, MA 01879 

YOUR REGISTRATION FEE INCLUDES:

COURSES						   CONFERENCE

Lectures			             Lectures
Course notebooks                    Poster session
Evening discussion sessions         Book of lecture & poster
Saturday reception                     abstracts
Continental breakfasts              Thursday reception
Lunches                             Two continental breakfasts
Dinners                             Two lunches
Coffee breaks                       One dinner              
                                    Coffee breaks


CANCELLATION POLICY:  Course fee, less $100, and the research
conference fee, less $60, will be refunded upon receipt of a written
request postmarked before March 31, 1992.  After this date no refund
will be made.  Registrants who do not attend and who do not cancel
in writing before March 31, 1991 are liable for the full amount of
the registration fee. You must obtain a cancellation number from the
registrar in order to make the cancellation valid.  

HOTEL RESERVATIONS: 

...Sheraton Tara, Nashua, NH (603) 888-9970, $60/night, plus tax   
   (single or double).
...Best Western, Nashua, NH (603) 888-1200, $44/night, single, plus 
   tax, $49/night, double, plus tax. 
...Stonehedge Inn, Tyngsboro, MA, (508) 649-4342, $84/night, plus   
   tax (single or double).

The special conference rate applies only if you mention the name and
dates of the meeting when making the reservation.  The hotels in
Nashua are located approximately five miles from the Wang Institute;
shuttle bus service will be provided to them.    

AIRLINE DISCOUNTS:

American Airlines is the official airline for Neural Networks. 
Receive 45% off full fare with at least seven days advance purchase
or 5% off discount fares.  A 35% discount applies on full fare
flights from Canada with an advance purchase of at least seven days.

Call American Airlines Meeting Services Desk at (800) 433-1790 and
be sure to reference STAR#SO252AM.  Some restrictions apply.  

STUDENT REGISTRATION:

A limited number of spaces at the courses and conference have been
reserved at a subsidized rate for full-time students.  These spaces
will be assigned on a first-come, first-served basis.  Completed
registration form and payment for students who wish to be considered
for the reduced student rates must be received by April 15, 1992.  



From hiebeler@Think.COM  Wed Nov  6 12:26:23 1991
Received: by mail.think.com; Wed, 6 Nov 91 12:26:30 -0500
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From: David Hiebeler <hiebeler@Think.COM>
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	id AA17806; Wed, 6 Nov 91 12:26:21 EST
Date: Wed, 6 Nov 91 12:26:21 EST
Message-Id: <9111061726.AA17806@passion.think.com>
To: x409@cutmcvax.cs.curtin.edu.au
Cc: ca@Think.COM
In-Reply-To: Ross Maloney's message of 2 Nov 91 04:03:14 GMT <x409.689054594@cutmcvax>
Subject: Re: Request for list of CA simulation source codes


  Several CA simulators have been mentioned.  Cellsim is one of them.
Currently, however, Cellsim only runs under the SunView windowing
system on Sun workstations.  I'm currently putting together a simple X
interface as time permits.  Below is a description of Cellsim.  Not
all of the features mentioned were fully implemented in the last
release of Cellsim (V2.5).  They are things that I have in my current
private version under development.  Hopefully within a couple of
months I will do another full release, which will have an X interface
as well as all of the features here.  (When I say "not fully
implemented" in V2.5, I mean that a couple of the features were
available only in very simple form, e.g.  V2.5 modules could only have
one pre- and post-processing routine each, while the next version lets
a module have any number of analysis routines).

  You can get Cellsim V2.5 via anonymous FTP from think.com
(131.239.2.1).  In the "pub/cellular-automata/cellsim" directory there
is a "cellsim_2.5.tar.Z" compressed tarfile.

  By the way, Cellsim is not a Thinking Machines product.  This is
something I worked on at Los Alamos National Lab with Chris Langton,
that I currently work on in my spare time.

  Here's a description of some of Cellsim's features.


Cellsim is a cellular automata simulation tool that runs on the Sun
workstation and Connection Machine CM-2.  It runs under the SunView
windowing system on the Sun, and uses C/Paris on the CM-2.


Some of the basic features of Cellsim are:

* Support of up to 256 states/cell.

* Direct support for the following neighborhoods:
    vonNeumann, Moore, Linear (1-D), Margolus

* Support for array sizes up to 512x512

* Ability to edit the array using the mouse and menus

* Ability to edit lookup-table rules, and generate lookup-tables via
Langton's "lambda parameter", or by specifying a rule-number for the 1-D
case.



Some of the nicer features of Cellsim are:

* Precomputed lookup-table rules are used when you have few neighbors
and states, so that the simulation will run more quickly; general
update-functions may be used to update the cells when the lookup-table
would be too large.  The update-functions are written in C.

* Analysis modules may be loaded in, separate from the rule that is
currently being used.  These are modules written in C, dynamically
linked in while running.

* Both rule-modules and analysis-modules let you define analysis
functions, in addition to "user-functions" which the user can select
from a menu.  Thus, you can build up a library of analysis modules, and
routines that perform useful operations on the array.  These things
can be independent of the rules, or some rule-modules may contain
such routines that are related to that specific rule.

* Any number of analysis routines may be loaded in at run-time.

* Computation may be performed locally, on the Sun workstation, or you
may attach to a Connection Machine CM-2 through the network.

* When attached to a CM-2, you may display the array on a CM
framebuffer if one is available, or you may ship the data back to the
Cellsim display panel, to display the array on the Sun (that is slow,
but still very useful when you are using a remote CM-2).

* The analysis-module concept become even more useful on the CM-2,
since you can generate enormous amounts of data per second on the
CM-2.  The analysis routines are written in C/Paris (as are the
update-functions), so that you do the analysis in parallel on the CM-2
as well.  You could also write routines that output data to the
DataVault, for example.  It should be possible to use C* with the CM-2
portion of Cellsim, since C* is built on top of C/Paris, but I have
not tried this yet.  Support for C* will probably be added in future
releases.

* If you are using lookup-table rules, you can use Cellsim with a
CM-2, without ever learning how to program the CM-2, since you can
create the lookup-table on the Sun, load it in on the Sun, and then
transmit it to the CM-2 and use it there.

* Even when you write C/Paris modules, you are spared the details of
creating geometries and virtual processors, and all the other little
things you would typically have to do to write CA code on the CM-2.
You only need to write the update-function.  (This advantage also
applies to writing CA code to run on the Sun -- Cellsim takes care of
most of the messy details, you just write a C module describing the
update rule).



Some sample modules

Examples of modules I've written are:

* Event-counters, to count cells with particular values.

* Routines to measure Shannon entropy and mutual information.

* A module that implements the hexagonal neighborhood (this actually
runs under the Moore neighborhood; the module makes a routine
available to your update-function that will fetch the appropriate
neighbors by mapping the hexagonal lattice onto a rectangular
lattice).

Other modules could be written, by myself or other people, and
collected into a library.



Plans

One of the most important things that needs to be done is to develop
an X interface to cellsim.

I'd like to make Cellsim work correctly with any size square array
(right now you must use a multiple of 4 size).  Non-square (e.g.
rectangular) arrays would also be nice, although support for that is
not planned for the near future.

Allow you to use larger lookup-tables (e.g. 16-state vonNeumann
neighborhood) on a CM-2 with large memory (CM-2 memory has gotten much
larger since I wrote the Cellsim CM-2 code).

I'm really hoping to add a CM-5 module as well.  That will be
especially convenient, since the exact same rule-module that you use
on a standalone Sun (or similar Unix box) could be used to run on a
CM-5.


--
Dave Hiebeler                  | Internet: hiebeler@think.com
Thinking Machines Corporation  | UUCP: {uunet,harvard}!think!hiebeler
245 First Street               | Bitnet: hiebeler%think.com@mitvma.bitnet
Cambridge, MA 02142  USA       | Phone:  (617) 234-4070 (work)

From cellular-automata-request@Think.COM  Wed Nov  6 15:12:49 1991
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Date: Wed, 6 Nov 91 11:14:12 PST
From: ghsvax!hal@uunet.UU.NET (Hal Finney)
To: ca@uunet.UU.NET
Subject: Cloud simulations?

(I am re-posting this because I don't think it got through the first
time.  If it is a duplicate, I apologize.)

I'd like to see a program which would show a hemisphere of the earth
covered with a realistic cloud pattern, where the clouds gradually
change over time.  I think this would be a pleasant program to have as
the background on a windowed system.

I think that a CA model might work to provide a rough approximation
to the dynamics of clouds.  I would envision first trying a 2-D
model, with each cell of the CA having quite a bit of state, such
as humidity, temperature, wind velocity, etc.  There would also
be outside influences on each cell: heat input, coriolis forces,
etc.  The new state of each cell would be a function of the states of
its neighbors plus the outside influences.  (I realize that this is
somewhat more state information than is commonly seen in CA models,
and that it almost becomes a solution to a set of PDE's using discrete
methods.  But I think the CA formulation is still valid.)

Does anyone know of any work that's been done along these lines?

One technical problem is the tiling of a sphere or hemisphere with a
2-D CA.  What approaches have worked for people doing spherical CA's?

Thanks for any suggestions.

Hal Finney
ghsvax!hal@uunet.uu.net

From cellular-automata-request@Think.COM  Fri Nov  8 03:50:01 1991
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Date: 6 Nov 91 22:36:35 GMT
From: Maurica_R_Fedors@cup.portal.com
Organization: The Portal System (TM)
Subject: Evolution & Optimization of Digital Organisms:NJ ASIS Mtg 11/19
Message-Id: <49733@cup.portal.com>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM


 
               DINNER MEETING:  NOVEMBER 19, 1991
                                
         EVOLUTION AND OPTIMIZATION OF DIGITAL ORGANISMS
                                
                                
 Speaker:               Thomas S. Ray
                        University of Delaware
 
Dr. Ray was featured in the August 27th New York Times article, 
"Lively creation blurs definition of life."  He has created a 
virtual computer, "Tierra," within which self-replicating computer 
creatures change spontaneously over time through evolution. He was 
recently awarded a prize by I.B.M.  for his contribution to 
supercomputing.
 
Dr. Ray will define "artificial life," state of the art and 
opportunities in this emerging field, his ongoing research and 
potential applications in the information area.
 
Synthetic organisms have been created based on a computer metaphor 
of organic life in which CPU time is the "energy"  resource and 
memory is the "material" resource.  Mutation generates new forms, 
and evolution proceeds by natural selection as different genotypes 
compete for CPU time and memory space.
 
Diverse ecological communities have emerged.  These digital 
communities have been used to experimentally examine ecological 
and evolutionary processes.
 
The computational issue is how to design a computer architecture 
and operating system that will support the natural evolution of 
machine code.  Dr. Ray is experimenting with variations on the 
successful architecture in order to find a good balance of 
computational power and evolvability. He also seeks to develop an 
analog to genetic engineering, in which application codes are 
inserted into the genomes of digital organisms and evolved to 
greater optimality or new functionality, using artificial 
selection. A more long term objective is to use digital organisms 
evolving freely or under artificial selection, as a source of new 
paradigms for the programming of massively parallel machines.
 
Location:               Sheraton Hotel
                        Woodbridge
 
Program:                5:30-6:30   Social Hour
 
****************Social hour sponsored by *********************
 
************ Commercial File and Storage, Inc. *****************
 
                        6:30-7:30   Dinner
                        7:30 +      Presentation & Discussion
 
 
Directions to the Sheraton
 
Take the Garden State Parkway to Exit 131A.
Follow around to the Second Traffic Light.  Turn Right at the 
light. (You will see Midlantic and Engelhard signs at the corner)
Pass Metro Park Train Station and proceed to the the First Traffic 
Light, Gill Lane.  
Turn right onto Gill Lane and follow it down to the Sheraton on 
your right.  (If you cross Route 1, you have passed it.)
 
 
The Sheraton is accessible by public transportation.  Take New 
Jersey Transit to Metro Park and take the Metro Park Loop Bus 
Route # 2 to the Sheraton (corner of Rte 1 & Gill La).  Departures 
are at 4:50, 5:10 & 5:30.
 
 --------------------------------------------------------------- 
 
Name:                                         Phone           
 
Affiliation:                                                  
 
Mailing Address:                                               
                                                             
Dinner Choice:
        Chicken Marsala        Vegetarian Platter
 
Cost:        ASIS                $25.00
             Nonmember           $27.00
             Student             $19.00
 
The Sheraton will provide babysitting services for our group but 
arrangements must be made at least a week prior to the event.  
The charge is $5.00/child/hour for the first child and 
$2/child/hour for each additional child. Please indicate if you 
want to participate.           
 
Please send reservations & checks payable to NJ ASIS by Nov 12th.
No cancellations will be accepted after that date.
 
Send reservations to:   Maurica Fedors         Phone:908-205-5269
                        Engelhard Corp
                           Technical Information Center
                        101 Wood Ave
                        Iselin, NJ 08830-0770
 

From cellular-automata-request@Think.COM  Fri Nov  8 04:46:48 1991
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Date: 7 Nov 91 14:44:25 GMT
From: ijp@doc.ic.ac.uk (I J Palmer)
Organization: Department of Computing, Imperial College, University of London, UK.
Subject: Re: 2d CA simulation programs
Message-Id: <1991Nov7.144425.21734@doc.ic.ac.uk>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM

In reply to a request for the locations of the sources for Cellular Automata
simulators for 2d arrays, there follows a description of just such a program
which I wrote during the first half of this year. The source should
be arriving in comp.sources.misc news group in the near future.

It is designed to run under X windows (X11R4), and will simulate domains
of cells of domain sizes from 5x5 cells to 512x512 cells (although these
limits can be changed). The domains can have one of three neighbourhood
connections (4,6 or 8 neighbours per cell) and each cell can be in any of
256 states (again this can be changed). The domain itself can be either
a torus ( top edge is joined to bottom edge, left edge joined to right edge)
or flat (the states of cells beyond the edges are undefined).

Each state can be given it's own colour, and the domain can be edited
using the mouse, as well as scrolled in four directions. The size of
displayed cells can also be changed, as well as the size of the domain,
during execution. The program keeps some statistics about the domain during
execution of rules, and these stats can be viewed during execution, whereby
they are constantly updated.

The program (which is called Scamper) also incorporates a (simple) language
which allows the specification of rules. Although the language is simple,
it is powerful enough to be able to specify any automaton that the simulator
can simulate (ie. 2dimentional, 4,6 or 8 neighbours, deterministic CA's).

As has been stated this program should soon be available in comp.sources.misc
but should you have problems obtaining it, I can e-mail it to people who
wish this. Mail to `ijp@doc.ic.ac.uk'. 

One final note, it was designed to run on a Sun 4 (Sparc), and I give no
assurances that it will run on anything else. (It is also a bit of a
memory eater, in order to gain speed).

Ian

-- 
                       |" /-\ |\| | (   |\| () \/\/
                            and avoid the rush
                            ------------------
                             ijp@doc.ic.ac.uk

From cellular-automata-request@Think.COM  Fri Nov  8 05:49:52 1991
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Date: 7 Nov 91 18:09:48 GMT
From: rich@elijah.ee.ic.ac.uk (Richard Evans)
Organization: Elec. Eng. Dept., Imperial College London
Subject: Announcement: ICANN 92 Final call for papers
Message-Id: <1991Nov7.180949.1620@cc.ic.ac.uk>
Newsgroups: comp.robotics,comp.theory.cell-automata,comp.theory.self-org-sys
Sender: ca-request@Think.COM
To: ca@Think.COM


   I C A N N   9 2 *** F I N A L   C A L L   F O R   P A P E R S ***
   -----------------------------------------------------------------

      The International Conference on Artificial Neural Networks
                 Brighton UK, 4th-7th September 1992

         Sponsored by the UK Department of Trade and Industry



                         Conference Chairs
                         -----------------
	                   Igor Aleksander
	                   John G Taylor


                           Program Chair
			   -------------
	                   Rolf Eckmiller


                   International Program Committee
		   -------------------------------
		Almeida (P)		 Amari (J)
		Angeniol (F)		 Babloyantz (B)
		Bounds (UK)		 Buttner (D)
		Caianiello (I)		 Croall (UK)
		Fallside (UK)		 Fogelman-Soulie (F)
		Fukushima (J)		 Garth (UK)
		Gielen (NL)		 Grossberg (USA)
		Hecht-Nielsen (USA)	 Hughes (UK)
		Kohonen (SF)		 Morasso (I)
		Murray (UK)		 Rolls (UK)
		Sherrington (UK)	 Simula (SF)
		Snyder (USA)		 Treleaven (UK)
		Von der Malsburg (D)	 Widrow (USA)


                             Tutorials
                             ---------

Grossberg (USA): Supervised and unsupervised learning, recognition
		 and prediction.
Kohonen (SF): The self organising map and vector quantisation
Rolls & Treves (UK): Biological approaches
Sharkey (UK): Natural language processing
Sherrington (UK): Statistical physics and Neural Nets
Widrow (USA): An overview of Neural Nets


                             Plenaries
                             ---------

Aleksander (UK): Whats new in '92 ?
Eckmiller (D): Biological vs. technical geometric mapping machines: when
	       will they ever learn?
Hinton (CAN): Shape recognition
Judd(USA): Complexity of learning - whats new ?
Kanarva (SF/USA): Associative memory models of the cerebellum
Kohonen (SF): Artificial Neural Networks: models, paradigms or methods ?
Murray (UK): What's new in hardware ?
TAylor (UK): From Neuron to cognition.
Werbos (USA): Neurocontrol: where do we stand in 1992 ?


                         Topics of Interest
                         ------------------

		Applications		Algorithms
		Architectures		Control Systems
		Associative Memories	Hardware and VLSI
		Cognitive models	Natural Language
		Hybrid Systems		Neuromathematics
		Industrial Systems	Robotics
		Learning Theory		Software
		Neurobiological Systems	Speech
		Pattern Recognition	Weightless Systems
		Sensorimotor Systems	Vision
		Signal processing	Other


                         Accent on quality
                         -----------------

The papers will be ranked in terms of evidence of NOVELTY and reviewers will
be asked to select those that rank highest in their topic for oral presentation.
The quality of poster sessions will also be kept high and the value of person-
to-person communication (rather than addressing an audience) in specialist areas
will be borne in mind by reviewers. We expect to accept 80-100 papers for oral
presentation and 200+ for poster presentation.

Both orally presented papers and poster papers which are accepted by the
referees will need to be written up fully (5pp) for prepublication in the
proceedings (Artificial Neural Networks II), to be published by Elsevier. See
the various deadlines below.


                        Submission of Papers
                        --------------------

             Deadline for submissions 15th February 1992
               Author notification: 15th March 1992
       Mats of accepted papers to publisher: 15th April 1992


Authors should submit two copies of an extended summary. Submissions should
be at most 3 pages of A4 in length with a fontsize of not less than 10-point.


The following MUST be included:

Title
Authors(s) and affiliation(s)
Full mailing address, email, fax etc.
Topic category from list above
A statement of the novelty of the paper
A reference to the last paper on the same topic and where it was submitted
A summary of the paper with a clear statement of which results are new
Relation to and references to relevant work in the topic done elsewhere


                        Submission address
                        ------------------

             Prof. Igor Aleksander,
             Department of Electrical Engineering,
             Imperial College,
             London SW7 2BT
             Fax: +44 71 823 8125
	     Tel: +44 71 225 8501
             Email:  i.aleksander@vaxa.cc.imperial.ac.uk

From cellular-automata-request@Think.COM  Fri Nov  8 08:43:57 1991
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Date: 8 Nov 91 04:41:40 GMT
From: todd@athena.elcom.nitech.ac.jp (Todd Law)
Organization: Nagoya Institute of Technology, Nagoya ,Japan.
Subject: CA - Where to start?
Message-Id: <TODD.91Nov8134136@athena.elcom.nitech.ac.jp>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM



Can anyone suggest a good starting point for
studying cell-automata?  Textbooks, key papers,
whatever?


Thanks a whole bunch.


Todd Law

--
$@%H%C%I!&%i!w0KF#8&5f<<(J.$@L>8E20(J$@9)6HBg3X(J
todd@juno.elcom.nitech.ac.jp (052-732-2111 ext. 2624)

From cellular-automata-request@Think.COM  Fri Nov  8 12:44:22 1991
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Date: 8 Nov 91 16:34:06 GMT
From: amhastings@ucdavis.edu (Alan Hastings)
Organization: ucdavis
Subject: Re: 2d CA simulation programs (summary)
Message-Id: <10364@ucdavis.ucdavis.edu>
Newsgroups: comp.theory.cell-automata
References: <1991Nov7.144425.21734@doc.ic.ac.uk>
Sender: ca-request@Think.COM
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Thanks for the replies I have received.  In addition to the program 
described in the recent post by ijp@doc.ic.ac.uk (I J Palmer), which works
on SUNS (SPARCS), there is CELLSIM for SUNS (also described in a recent post)
 which now works under SUNVIEW, but is being ported to X.  There is also
something called xlife.

For the macs, a program called LifeLab is availble at all the usual mac
archives.

Alan Hastings
amhastigns@ucdavis.edu


From cellular-automata-request@Think.COM  Sat Nov  9 12:44:07 1991
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Date: 9 Nov 91 16:56:45 GMT
From: dahlhaus@cis.ohio-state.edu (kevin dahlhaus)
Organization: The Ohio State University Department of Computer and Information Science
Subject: Where can I upload a relevant program
Message-Id: <9111091656.AA09441@skink.cis.ohio-state.edu>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
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There was a recent question regarding the availability
of programs relating to cellular automata. I have a 
program called 'protozoa' which is based on the 
May 1989 Computer Recreations column in Scientific
American. It runs on IBM PC's with CGA or better, and
the author is not asking money for it.

The program simulates the process of natural selection.

What would be the best place to upload it{

From cellular-automata-request@Think.COM  Mon Nov 11 06:44:21 1991
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Date: 11 Nov 91 04:54:39 GMT
From: todd@hera.elcom.nitech.ac.jp (Todd Law)
Organization: Nagoya Institute of Technology, Nagoya ,Japan.
Subject: Re: CA - Where to start?
Message-Id: <TODD.91Nov11135432@hera.elcom.nitech.ac.jp>
Newsgroups: comp.theory.cell-automata
References: <TODD.91Nov8134136@athena.elcom.nitech.ac.jp>
Sender: ca-request@Think.COM
To: ca@Think.COM


The following is a summary of the responses to my request for 
a starting point to study cellular automata, for anyone interested:

Books
-----

'Artificial Life', by Christopher Langton.

'Emergent Computation', edited by Stephannie Forrest, MIT Press.

'The Armchair Universe', by A.K. Dewdney.

'Cellular Automata', edited by Gutowitz, proceedings of a 1989 conference
in Los Alamos.

'Theory and Applications of Cellular Automata', S. Wolfram, World Scientific.
(recommended as one of the best books)

'Cellular Automaton Machines', Margolus and Toffuli, MIT Press
(recommended as one of the best books)



Programs
--------

'CA Lab' for the IBM PC, by Rudy Rucker and John Walker, Autodesk, $59.95.
(order from Autodesk, 2320 Marinship Way, Sausalito CA 94965, put
"Attention: Science Series Order" on the envelope. Or dial (800) 688-2344.

'CASim' for the Mac, by Ken Karakotsios (karakots@apple.com).



Relevant Journals
-----------------

'Physica-D', 

'Complex Systems 4'
'Complex Systems 5'

'Commun. Math. Phys.'

'Int'l J. Theo. Phys'

(Burton Voorhees has published on simple ca's in all of these journals:
see Physica D, 31 (1988) pp. 135-140, Physica D, 45 (1990) p. 26-35,
Comm. Math. Phys. 117 (1988) pp. 431-439, Complex Systems 4 (1990) 
pp. 587-597, Complex Systems 5 (1991) pp.169-182, and
Int'l J. Theo. Phys. 26 (11) (1989) pp. 1387-1386)


=========================================================================

The information came from a total of seven people.
Thanks for everone's contribution.


Todd Law
Nagoya Institute of Technology

--
$@%H%C%I!&%i!w0KF#8&5f<<(J.$@L>8E209)6HBg3X(J
todd@juno.elcom.nitech.ac.jp (052-732-2111 ext. 2624)

From cellular-automata-request@Think.COM  Mon Nov 11 19:44:37 1991
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Date: Tue, 12 Nov 1991 00:04:41 GMT
From: levine@procyon (Lenore Levine)
Organization: University of Illinois at Urbana
Subject: Surjective Cellular Automaton Rules
Message-Id: <1991Nov12.000441.2677@ux1.cso.uiuc.edu>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM


Has anyone made a list of surjective one-dimensional cellular 
automaton rules (using more than two colors or with a radius 
greater than one)?
Lenore Levine
levine@symcom.math.uiuc.edu

From cellular-automata-request@Think.COM  Tue Nov 12 08:42:20 1991
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From: lfw%megsc.dnet@gte.com (Larry F. Wood)
To: "ca@Think.com"%bunny.dnet@gte.com
Cc: lfw@gte.com
Subject: X11/Decstation version of cellsim

Does anyone know of a version of cellsim that runs on the Decstation
3100 running Ultrix with Decwindows/X11?

Thanks,

Larry Wood

lfw1@gte.com

From cellular-automata-request@Think.COM  Tue Nov 12 12:47:30 1991
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Date: Tue, 12 Nov 1991 15:07:38 GMT
From: james@panix.com (James Britt)
Organization: PANIX Public Access Unix, NYC
Subject: Re: CA - Where to start?
Message-Id: <1991Nov12.150738.29833@panix.com>
Newsgroups: comp.theory.cell-automata
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I would like to add to the list the book Complexity, Entropy and
the Physics of Information, edited by Wojciech H. Zurek, from
Addison - Wesley.  It is a collection of papers from the Santa Fe
Institute studies in the sciences of complexity.

The Santa Fe Institute also publishes a magazine (quarterly? I forget) 
which includes announcements of books, procedings, conferences and the
like regarding alife and cellular automata, among other things.

-- 
******************************************************************************
James Britt, Ronin Socratic                       "Hack the wetware!"
james@panix.com
******************************************************************************

From cellular-automata-request@Think.COM  Tue Nov 12 13:00:59 1991
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Date: Tue, 12 Nov 91 09:33:44 PST
From: autodesk!air!rudy@fernwood.mpk.ca.us (Rudy Rucker)
Message-Id: <9111121733.AA00568@air.acad>
To: ca@Think.COM
Subject: Ray's Tierra software


For those interested in Thomas Ray's Tiera Simulator, I see that
this is now available as a PC product for $65 + $3.50 P&H from
Media Magic, P.O. Box 507, Nicasio CA 94946!

From cellular-automata-request@Think.COM  Tue Nov 12 13:03:37 1991
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From: autodesk!air!rudy@fernwood.mpk.ca.us (Rudy Rucker)
Message-Id: <9111121731.AA00564@air.acad>
To: ca@Think.COM
Subject: cloudlike CAs


Hal Finney writes:
----------------
I think that a CA model might work to provide a rough approximation
to the dynamics of clouds.  I would envision first trying a 2-D
model, with each cell of the CA having quite a bit of state, such
as humidity, temperature, wind velocity, etc.  There would also
be outside influences on each cell: heat input, coriolis forces,
etc.  The new state of each cell would be a function of the states of
its neighbors plus the outside influences.  (I realize that this is
somewhat more state information than is commonly seen in CA models,
and that it almost becomes a solution to a set of PDE's using discrete
methods.  But I think the CA formulation is still valid.)

Does anyone know of any work that's been done along these lines?

One technical problem is the tiling of a sphere or hemisphere with a
2-D CA.  What approaches have worked for people doing spherical CA's?
       
-----------------------

One CA I've worked with that gives an effect somewhat like global
weather is to use Griffeath's Eat rule in it's random form with
about 64 states.  That is each cell changes to the next state MOD 64
if one of its neighbors is in that state.  The program uses a
fast randomizer so that each cell looks at one random neighbor each
update.  If you seed the grid with random cells from states 0 to 63,
not much happens.  But if you cut out a disk and color all those cells
to 0 state, then 1 state encroches into the disk, then 2, then 3, and
so on.  This gives, as I say, a visual effect reminiscent of clould
flow.  You can do this in CA Lab using an owncode rule, though it's
not that simple to set up.

The idea allowing a spherical grid for your CA world is a really
nice one, and if we redo CA lab, I'd like to build that in as an
option, if I could figure out a good way to do it.  The big problem
with a sphere, of course, is that you can't have 3x3 square neighbor
hoods everywhere, so there will be some kind of anomalous kludge
at the poles.  Also the equator cells would be larger than the
other cells.  I guess you could go to some kind of Fullerene
sphere tesselation with triangles.  For many rules, having 3 or
6 neighbors instead of 4 or 9 wouldn't make that much difference,
e.g. for the rule just outlined above it wouldn't make much difference,
so far as I can see.  I know that Hans Moravec invented a very nice
suite of Life-like rules based on hexagonal grids.

From cellular-automata-request@Think.COM  Fri Nov 15 06:45:35 1991
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Date: 15 Nov 91 10:35:06 GMT
From: evenson@hitl.washington.edu (Mark Evenson)
Organization: R+D Hipsters @ virtual HITLab, Ithaca
Subject: Re: Cellular Automata program for Macs
Message-Id: <EVENSON.91Nov15023506@jabberwock.hitl.washington.edu>
Newsgroups: comp.theory.cell-automata
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In article <1991Nov3.160346.12848@milton.u.washington.edu> jesjones@milton.u.washington.edu (Jesse Jones) writes:

   A while back someone posted an article asking about CA programs for
   Macs. I should have replied then but I'm brand new to Usenet so I
   didn't. I wrote a program called LifeMaker last summer. The latest
   version is 2.0 (which added the rule editor). The program has been
   uploaded to CompuServe, BIX, and probably other places. LifeMakers
   features include:

	Does a copy of LifeMaker exist via a site accessible to the
Internet?  I tried to find a site via archie, but came up negative (first
instance for archie not knowing something for me!).  Any ideas?

From cellular-automata-request@Think.COM  Sat Nov 16 10:49:01 1991
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Date: 16 Nov 91 14:55:26 GMT
From: scott@scotty.life.uiuc.edu
Organization: University of Illinois at Urbana
Subject: Re: Cellular Automata program for Macs
Message-Id: <scott.690303326@scotty>
Newsgroups: comp.theory.cell-automata
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LifeMaker is available on mac.archive.umich.edu,
in the directory /mac/graphics/math/lifemaker2.0.cpt.hqx.


Hope this helps!

--
macaddress:				Scott_Howard@QMS1.life.uiuc.edu
unixaddress:				scott@darwin.life.uiuc.edu

_____________Why have an ordinary .sig when you can be bland?_____________

From cellular-automata-request@Think.COM  Tue Nov 19 17:47:15 1991
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Date: 19 Nov 91 21:55:46 GMT
From: steve@gabriela.Tymnet.COM (Steve Sandke)
Organization: BT North America, San Jose, CA
Subject: Looking for CA classes in C++
Message-Id: <973@tymix.Tymnet.COM>
Newsgroups: comp.theory.cell-automata
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I'm looking for a class (or more likely, a set of classes) in C++ that would implement CAs.

Any ideas?

-- 
-------------------
Steve Sandke
steve@orchid.tymnet.com

From cellular-automata-request@Think.COM  Wed Nov 20 15:36:15 1991
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From: lfw%megsc.dnet@gte.com (Larry F. Wood)
To: "ca@Think.COM"%bunny.dnet@gte.com
Subject: CA software for PC

Could anyone suggest some software for the PC to run CA experiments?

From cellular-automata-request@Think.COM  Thu Nov 21 06:04:41 1991
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From: Pedro Paulo Balbi de Oliveira <pedrob@cogs.sussex.ac.uk>
Date: Thu, 21 Nov 91 10:25:57 GMT
To: cellular-automata@Think.COM
Subject: Cellsim under OpenWindows
Cc: pedrob@cogs.sussex.ac.uk

There are several problems when running Cellsim-2.5
under OpenWindows-2.0. For example, when loading a new
rule or a new colour-map, there is a long elapsed time
(about 30sec) between typing a character and its
displaying on the screen.

Has anyone managed to circumvent these problems by 
adding any command ".openwin-init", changing the C-source
or whatever?

Thanks for any pointer.

..Pedro

  Pedro Paulo Balbi de Oliveira   | School of Cognitive and Computing Sciences
  Email: pedrob@cogs.sussex.ac.uk | The University of Sussex - COGS PG/ph
  Phone: (44) 273 606-755, x 3072 | Falmer, Brighton BN1 9QH - E.Sussex
  Fax  : (44) 273 678-188         | England

From cellular-automata-request@Think.COM  Fri Nov 22 14:36:18 1991
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From: J_BATES@UNHH.UNH.EDU (John Bates)
Message-Id: <911122143527.23c02b5a@UNHH.UNH.EDU>
Subject: k = 3, r = 1, 1-D CA
To: cellular-automata@Think.COM
X-Vmsmail-To: SMTP%"cellular-automata@Think.COM"

Is anyone aware of any extensive studies done
on k = 3, r = 1 (3 states-per-cell, nearest neighbor)
one-dimensional CA? Also, are there any results
with regard to the computational capability
of this class of CA?

John Bates
Physics Department
University of New Hampshire
j_bates@unhh.unh.edu

From cellular-automata-request@Think.COM  Fri Nov 22 15:14:59 1991
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Date: Fri, 22 Nov 1991 15:16-0500
From: Allan C. Wechsler <ACW@YUKON.SCRC.Symbolics.COM>
Subject: k = 3, r = 1, 1-D CA
To: J_BATES@UNHH.UNH.EDU, cellular-automata@Think.COM
In-Reply-To: <911122143527.23c02b5a@UNHH.UNH.EDU>
Message-Id: <19911122201606.6.ACW@PALLANDO.SCRC.Symbolics.COM>

Perhaps Wolfram has done a survey of these, but only of what he calls
"totalistic" rules.  In my opinion this restriction is unmotivated,
except perhaps by expediency.  A totalistic rule assigns an arbitrary
numerical code to each state, and the outcome state of a cell is a function
of the sum of the codes of the states in the neighborhood of that cell.

There are 3^10 = 59049 totalistic rules with (k,r) = (3,1), compared
with 3^27 = 7625597484987 rules in all.

A research program exploring the computational capability of these
automata should begin by trying to prove large classes of them
non-universal.

From cellular-automata-request@Think.COM  Sat Nov 23 07:47:33 1991
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Date: 23 Nov 91 03:47:25 GMT
From: sieburg@euclid.ucsd.edu (Hans Sieburg)
Subject: Re: CA software for PC
Message-Id: <25832@sdcc6.ucsd.edu>
Newsgroups: comp.theory.cell-automata
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In article <9111202036.AA23749@bunny.gte.com>, lfw%megsc.dnet@gte.COM (Larry F. Wood) writes:
> Could anyone suggest some software for the PC to run CA experiments?

From cellular-automata-request@Think.COM  Sat Nov 23 13:47:52 1991
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Date: 22 Nov 91 22:40:26 GMT
From: jf41+@andrew.cmu.edu (Jonathan R. Ferro)
Organization: Carnegie Mellon, Pittsburgh, PA
Subject: WireWorld, anyone?
Message-Id: <Ud=MROe00Vp9A2uEhd@andrew.cmu.edu>
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Quite some time ago on this group there was a discussion of a cellular
automata referred to as WireWorld, so named because it consisted of
pulses travelling along lines of "wire" cells which were delineated by
permanently dead cells.  I specifically remember the ability to form a
small configuration of wire cells which behaved like a diode with
respect to the pulses.

Having moved up to hardware which is competent to think about these
things I would like to play around with this again, but I have forgotten
the update rule and all of the patterns.  Could someone please send me
some information to get me (re)started or direct me to an archive of
some sort?  Thanks in advance.

--
Jon Ferro		MIT Transportation Modelling Research Center
jf41+@andrew.cmu.edu	"We can hack it!"

From cellular-automata-request@Think.COM  Sat Nov 23 18:48:13 1991
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Date: Sat, 23 Nov 91 23:25:56 GMT
From: yxt3@po.CWRU.Edu (Yoshiyasu Takefuji)
Organization: Case Western Reserve University, Cleveland, Ohio, (USA)
Subject: A new book "Neural Network Parallel Computing"
Message-Id: <1991Nov23.232556.13713@usenet.ins.cwru.edu>
Newsgroups: comp.theory.cell-automata
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NEW FROM KLUWER ACADEMIC PUBLISHERS

Neural Network Parallel Computing

By Yoshiyasu Takefuji, Case Western Reserve University, USA
1992 ISBN 0-7923-9190-X Cloth 240 pages $65.00

Neural Network Parallel Computing is the first book and the only single
book available for the professional on neural network computing for
optimization problems. This introductory book is for experts in a
variety of areas including parallel computing, neural network computing,
computer science, communications, graph theory, computer aided design
for VLSI circuits, molecular biology, management science, and operations
research, as well as for the novice in these areas.

Neural Network Parallel Computing provides real applications and
real-world examples. The computational power of neural network computing
is demonstrated by solving numerous problems such as N-queen, crossbar
switch scheduling, four-coloring and k-colorability, graph planarization
and channel routing, RNA secondary structure prediction, knight's tour,
spare allocation, sorting and searching, and tiling.

Neural Network Parallel Computing presents a major breakthrough in
science as well as a variety of engineering fields. This book is an
excellent reference for researchers in all areas covered in this book.
This text may also be used as a senior or graduate level course on the
topic.



Contents

Preface
Acknowledgements

Chapter 1       Neural network models and N-queen problems
        1.1 Introduction
        1.2 Mathematical neural network models
        1.3 N-queen neural network 
        1.4 General optimization programs
        1.5 N-queen simulation programs 
        1.6 References
        1.7 Exercises

Chapter 2       Crossbar switch scheduling problems
        2.1 Introduction
        2.2 Crossbar scheduling problems and N-queen problems
        2.3 References
        2.4 Exercises

Chapter 3       Four-coloring map problems and k-colorability problems
        3.1 Introduction
        3.2 Four-coloring neural network
        3.3 K-colorability neural network
        3.4 References
        3.5 Exercises

Chapter 4       Graph planarization problems
        4.1 Introduction
        4.2 Neural representation and motion equations
        4.3 References
        4.4 Exercises

Chapter 5       Channel routing problems
        5.1 Introduction
        5.2 Graph planarization and channel routing
        5.3 References
        5.4 Exercises

Chapter 6       RNA secondary structure prediction
        6.1 Introduction
        6.2 Maximum independent set problems
        6.3 Predicting the secondary structure in ribonucleic acids
        6.4 Graph planarization and RNA secondary structure prediction
        6.5 References
        6.6 Exercises

Chapter 7       Knight's tour problems
        7.1 Introduction
        7.2 Neural representation and motion equations
        7.3 References
        7.4 Exercises

Chapter 8       Spare Allocation problems
        8.1 Introduction
        8.2 Neural representation and motion equations
        8.3 References
        8.4 Exercises
             
Chapter 9       Sorting and Searching
        9.1 Introduction
        9.2 Sorting
        9.3 Searching
        9.4 References

Chapter 10      Tiling problems
        10.1 Introduction
        10.2 Neural representation and motion equations
        10.3 References
        10.4 Exercises

Chapter 11      Silicon neural networks
        11.1 Introduction
        11.2 Analog implementations
        11.3 Digital implementations
        11.4 References
        11.5 Exercises

Chapter 12      Mathematical background of the artificial neural network
        12.1 Introduction and four neuron models
        12.2 Why is the decay term harmful?
        12.3 Basic analog convergence theorem and proof
        12.4 Discrete sigmoid neural network convergence theorem and proof
        12.5 McCulloch-Pitts neural network convergence theorem and proof
        12.6 Hysteresis McCulloch-Pitts neural network convergence theorem 
        and proof
        12.7 Maximum neural network convergence theorem and proof
        12.8 Other neuron models
        12.9 References

Chapter 13      Forthcoming applications
        13.1 Introduction
        13.2 Time slot assignment in TDM hiearchical switching system
        13.3 Broadcast scheduling in packet radio networks
        13.4 Module orientation problems
        13.5 Maximum clique problems

Chapter 14      Conjunctoids and  artificial learning
        14.1 Introduction
        14.2 Multinomial conjunctoid concepts
        14.3 Multnomial conjunctoid circuitry
        14.4 References
             
Subject index


To order the book by mail
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From cellular-automata-request@Think.COM  Mon Nov 25 08:49:18 1991
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Date: 25 Nov 91 11:38:51 GMT
From: torbenm@diku.dk (Torben AEgidius Mogensen)
Organization: Department of Computer Science, U of Copenhagen
Subject: Re: WireWorld, anyone?
Message-Id: <1991Nov25.113851.16760@odin.diku.dk>
Newsgroups: comp.theory.cell-automata
References: <Ud=MROe00Vp9A2uEhd@andrew.cmu.edu>
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jf41+@andrew.cmu.edu (Jonathan R. Ferro) writes:

>Quite some time ago on this group there was a discussion of a cellular
>automata referred to as WireWorld, so named because it consisted of
>pulses travelling along lines of "wire" cells which were delineated by
>permanently dead cells.  I specifically remember the ability to form a
>small configuration of wire cells which behaved like a diode with
>respect to the pulses.

>Having moved up to hardware which is competent to think about these
>things I would like to play around with this again, but I have forgotten
>the update rule and all of the patterns.  Could someone please send me
>some information to get me (re)started or direct me to an archive of
>some sort?  Thanks in advance.

>--
>Jon Ferro		MIT Transportation Modelling Research Center
>jf41+@andrew.cmu.edu	"We can hack it!"

There are these types of cells:

Background:	.
Wire:		+
Electron head:	#
Electron tail:	*

The rules are:

1) Background never changes.

2) Electron head always change to electron tail.

3) Electron tail always change to wire.

4) The next state of a wire cell is determined by counting the number
   of wire heads in the 8 neighbour cells. If there is one or two, the
   next state is an electron head, otherwise it remains a wire.

A few examples:

Diode:

	..........	A signal from right will be stopped.
	....++....	A signal from left will pass through.
	+++++.++++
	....++....
	..........

Or:

	....+.....	A signal from top or bottom (or both)
	....+.....	will cause a signal to leave at right.
	...+++++++	No signal will pass through from top
	....+.....	to bottom or vice versa.
	....+.....

Xor:

	....+.....	A signal from top or bottom (not both)
	...++++...	will cause a signal to leave at right.
	...+.+++++	No signal will pass through from top
	...++++...	to bottom or vice versa.
	....+.....

Power (clock):

	..........	A signal will leave at right every 8
	...+++....	cycles. The period can be modified by
	..+...++++	changing the length of the loop.
	...+*#....
	..........

Not (clocked) (has to be):

	..........	A correctly timed signal from left (shown)
	+*#+......	will cancel the signal that would otherwise
	....+.....	leave at right every 4 cycles.
	...+++....
	....+.....
	...+.+++++
	..+.......
	.*.+......
	..#.......

Note that all logical functions that has a non-zero result when
all inputs are zero requires a power source, and thus a clock.
If the clock was replaced by another input we would have a
"B and not A" gate. By adding a not gate we can obtain an and
gate. It is, however, possible to obtain a non-clocked and gate.
I leave this as an exercise (hint: you can use an xor and a
"B and not A").

Theorem: All n-ary functions that has a zero result when all inputs
are zero can be implemented without a clock.

Proof: All binary functions that maps (0,0) to 0 can be implemented
without a clock. (I leave this as an exercise). Wire-crossing can be
implemented without a clock. (Another exercise (hint: 3 xors)). Any
n-ary function that maps (0,...,0) to 0 can be constructed by
combining binary functions that maps (0,0) to 0. (Essentially by
tabulating the arguments that map to 1 and express this as a logical
formula).

Interesting exercises:

1) A memory cell.

2) A bit-serial adder (non-powered). Try to keep cycle time low.
   My brother did this with a very low cycle count. I think it was 4.

3) A shift-register.

Hope this helps.

	Torben Mogensen (torbenm@diku.dk)

From cellular-automata-request@Think.COM  Mon Nov 25 12:49:09 1991
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Date: 25 Nov 91 14:52:33 GMT
From: james@panix.com (James Britt)
Organization: PANIX Public Access Unix, NYC
Subject: Re: CA software for PC
Message-Id: <1991Nov25.145233.14597@panix.com>
Newsgroups: comp.theory.cell-automata
References: <9111202036.AA23749@bunny.gte.com>
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In <9111202036.AA23749@bunny.gte.com> lfw%megsc.dnet@gte.COM (Larry F. Wood) writes:

>Could anyone suggest some software for the PC to run CA experiments?

CA LAB form AutoDesk comes to mind. I haven't used it, butthe demo
looks good.  I believe it's about $60.00.

James

-- 
******************************************************************************
James Britt, Ronin Socratic                       "Hack the wetware!"
james@panix.com
******************************************************************************

From cellular-automata-request@Think.COM  Tue Nov 26 21:49:26 1991
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Date: 27 Nov 91 00:42:21 GMT
From: tiktok@milton.u.washington.edu (steve feldon)
Organization: University of Washington
Subject: Re: WireWorld, anyone?
Message-Id: <1991Nov27.004221.3425@milton.u.washington.edu>
Newsgroups: comp.theory.cell-automata
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To: ca@Think.COM

torbenm@diku.dk (Torben AEgidius Mogensen) writes:

>jf41+@andrew.cmu.edu (Jonathan R. Ferro) writes:

>>Quite some time ago on this group there was a discussion of a cellular
>>automata referred to as WireWorld, so named because it consisted of
>>pulses travelling along lines of "wire" cells which were delineated by
>>permanently dead cells.  I specifically remember the ability to form a
>>small configuration of wire cells which behaved like a diode with
>>respect to the pulses.

I have implemented it for color Macintoshs, as a document for the
program LifeMaker.  If you are interested in playing with it,
LifeMaker is available for anonymous ftp from mac.archive.umich.edu,
in the directory /mac/graphics/math/lifemaker2.0.cpt.hqx.  The text of
my WireWorld program is at the end of this message.

BTW, LifeMaker seems an interesting and powerful CA description package.
I was able to get WireWorld up and running about half an hour after
getting the program....

>Interesting exercises:

>1) A memory cell.

>2) A bit-serial adder (non-powered). Try to keep cycle time low.
>   My brother did this with a very low cycle count. I think it was 4.

>3) A shift-register.

If anyone has done these, I'd love to see them.

WireWorld for LifeMaker 2.0
--------------------------------cut here---------------------------------------
RULE WireWorld (center, north, NE, east, SE, south, SW, west, NW)
   VAR new, temp
BEGIN
   IF center=0 THEN 
      new:=0
   ELSIF center=3 THEN 
      temp:=(north=2)+(NE=2)+(east=2)+(SE=2)+(south=2)+(SW=2)+(west=2)+(NW=2)
      IF (temp=1) OR (temp=2) THEN
         new:=2
      ELSE
         new:=3
      END
   ELSIF center=1 THEN
      new:=3
   ELSIF center=2 THEN 
      new:=1
   END
   RETURN new
END
-- 
==============================================================================
Steve Feldon             | These are MY ideas | "Don't stop thinking about
tiktok@u.washington.edu  | and opinions. :-]  |  tomorrow." - Fleetwood Mac

From cellular-automata-request@Think.COM  Wed Nov 27 08:49:22 1991
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Date: 27 Nov 91 15:15:00 GMT
From: mikouh@Kontu.cc.utu.fi
Organization: University of Turku, Finland
Subject: Life books, again?
Message-Id: <1991Nov27.151500.1@kontu.utu.fi>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
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This must be FAQ but I didn't find it so...

I am looking for books & articles concerning Conway's "Life".
Especially I am interested in the universality proofs and gardens of Eden.

At the moment I know only:

Berlekamp,Conway,Guy: Winning ways...
Gardner: articles in Sci. Amer.
Toffoli,Margolus: Cellular automata machines

If there is interest I will summarize.

Thank you for your help.

Mika Kouhia
<mikouh@euroni.utu.fi>

From cellular-automata-request@Think.COM  Wed Nov 27 11:49:28 1991
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Date: 27 Nov 91 18:59:51 GMT
From: bokkie@uctvax.uct.ac.za
Organization: University of Cape Town
Subject: CONWAY'S GAME "LIFE" - SOFTWARE?
Message-Id: <201188.2933cf07@uctvax.uct.ac.za>
Newsgroups: comp.theory.cell-automata
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Does anybody out there know about a computer program
for John Horton Conway's "Life" game, as described
in Scientific American, 1970, 223(4) by Martin Gardner?
(That was before the days of PC's)

I would like to get a working program after reading 
about this game in Dan Dennett's book _The Intentional
Stance_.  I have been experimenting with PROLOG code
to make my own, but there must be sophisticated 
versions around now.

Please let me know how I could get the code, or the
software.

Frank Bokhorst          EMAIL: BOKKIE@UCTVAX.UCT.AC.ZA
Dept. of Psychology
University of Cape Town

From cellular-automata-request@Think.COM  Thu Nov 28 04:49:34 1991
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Date: 28 Nov 91 08:22:01 GMT
From: dekorte@vsserv.scri.fsu.edu (Stephen L. DeKorte)
Organization: SCRI, Florida State University
Subject: Optimization using CA (need sources)
Message-Id: <5734@sun13.scri.fsu.edu>
Newsgroups: comp.theory.cell-automata
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 I'm looking for literature on using celluar automata to solve
optimization problems.

All/any help much appreciated,
 Steve DeKorte (dekorte@ibm4.scri.fsu.edu) 

From cellular-automata-request@Think.COM  Thu Nov 28 16:50:26 1991
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Date: 28 Nov 91 20:38:20 GMT
From: sotoc@cdl02.me.msu.edu (Ciro Soto)
Organization: College of Engineering, Michigan State University
Subject: Re: Optimization using CA (need sources)
Message-Id: <1991Nov28.203820.408@msuinfo.cl.msu.edu>
Newsgroups: comp.theory.cell-automata
References: <5734@sun13.scri.fsu.edu>
Sender: ca-request@Think.COM
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I am also interested in this topic. I do not know anything about
CA. I need some introductory textbook.

Thanks in advance

Ciro Soto

From cellular-automata-request@Think.COM  Fri Nov 29 12:50:49 1991
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Date: 27 Nov 91 21:06:04 GMT
From: uuz@academ.alma-ata.su (Zykov Yuri Y.)
Organization: Academy of Scinces of Kazakhstan
Subject: CA chains: generator of landscape images
Message-Id: <AByY0DfmR2@academ.alma-ata.su>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
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I think CA can create good images of natural landscapes.
The problem consists in formation of color texture, which the human eye 
perceives as a some class of landscapes (far wood, rocky mountains,etc).

One in a possible path is to construct the CA chain from various CAs, in 
which the finished state of CA(n) is starting state for CA(n+1).  
The variation of total combination of rules and configurations of CAs in 
each chain link gives the greater a chance to do transformation of 
information than this is possible in framework of one CA.

For example: six link CAs chain with square grid which generates the color 
texture of rocky mountains.

CA(1)  has 5 of states in each cell. On two dimensional lattice is realized 
       the growth cluster according small changed rules of Iden's fractal.
CA(2)  has a some hundreds of states in each cell.CA(2) treats the results 
       CA(1) into two dimensional lattice in which the number of state in 
       cell is symbolic altitude of this cell.
CA(3)  has a some hundred of states in each cell. Purpose of CA(3) is to give 
       by symbolic altitude gradient between neighbouring cells necessary 
       character (from rocky mountains to sloping mounds).
CA(4)  realizes the transition to three dimensional lattice with two of state 
       in cell: 0 - cell belong to mountains; 1 - cell don't ones.
CA(5)  has three dimensional square grid . The number of state in cell is 
       equal by number of colors in pallete of picture. Analysis of 
       environment and choice of state (color) for each cell are come.
CA(6)  has two dimensional square grid. The number of state in cell is equal 
       by number of colors in pallete of picture. The transition of three 
       dimensional color lattice to it two dimensional projection is come.

Structure of chain CA are complex therefore I wrote the special programs for 
IBM PS in TyrboPascal.The 90% of count time was used in CA(1).The intel-80286
count time of CA(1) array with size 300 x 100  is equal about one hour. 
This array can be by source for infinity diversity of mountains forms.

Does anyone know of any work that's been done along these lines ?

In appendix you can find the arhived file with fragment of rocky mountains 
image .It can be looked on IBM PS with monitor VGA.
____________________________________________________________________________
Alexei Terekhov
Institute of Space Researchs
Alma-Ata 480021 USSR

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MK]8N^,KI@^Y9%FP2.W

From cellular-automata-request@Think.COM  Sun Dec  1 00:50:55 1991
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Date: 1 Dec 91 05:42:10 GMT
From: rthomson@mesa.dsd.es.com (Rich Thomson)
Organization: Design Systems Division, Evans & Sutherland, SLC, UT
Subject: Re: CONWAY'S GAME "LIFE" - SOFTWARE?
Message-Id: <1991Dec1.054210.21850@dsd.es.com>
Newsgroups: comp.theory.cell-automata
References: <201188.2933cf07@uctvax.uct.ac.za>
Sender: ca-request@Think.COM
To: ca@Think.COM

In article <201188.2933cf07@uctvax.uct.ac.za>
	bokkie@uctvax.uct.ac.za writes:
>Does anybody out there know about a computer program
>for John Horton Conway's "Life" game, as described
>in Scientific American, 1970, 223(4) by Martin Gardner?
>(That was before the days of PC's)

You can try xlife (current version is 2.0, I believe).  This is a good
life program for the X Window System.  It should be available by anonymous
FTP on export.lcs.mit.edu.  Look in the contrib directory.

						-- Rich
-- 
	Repeal the personal income tax; vote Libertarian in 1992.
	    Disclaimer: I speak for myself, except as noted.
UUCP: ...!uunet!dsd.es.com!rthomson			Rich Thomson
Internet: rthomson@dsd.es.com	IRC: _Rich_		PEXt Programmer

From cellular-automata-request@Think.COM  Mon Dec  2 05:51:32 1991
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Date: 2 Dec 91 10:34:14 GMT
From: ksagouro@immd4.informatik.uni-erlangen.de (Konstantinos Agouros)
Organization: CSD., University of Erlangen, Germany
Subject: Genetic Algorithms
Message-Id: <1991Dec2.103414.22303@informatik.uni-erlangen.de>
Newsgroups: comp.theory.cell-automata
Sender: ca-request@Think.COM
To: ca@Think.COM

Hello

I do have a class about genetic algorithms. The only literature we have is the
book by Goldberg. I would like to get some more info about that theme. I am
interested in book titles, ftp'able Papers etc. 
As I am not reading this newsgroup frequently I would be glad if you could 
resond to me by email.

Konstantin
---
Snail: Konstantinos Agouros Erlanger Str. 11, 8521 Spardorf, Germany
Email: ksagouro@immd4.informatik.uni-erlangen.de
Phone:+49 9131 501103 or +49 2175 3353
IRC:  Elwood_G
-------------------------------------------------------------------------------
"There is a viaduct.","Why a Duck, why not a chicken?" Groucho&Chico Marx

From cellular-automata-request@Think.COM  Mon Dec  2 08:52:02 1991
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Date: 2 Dec 91 13:00:21 GMT
From: angelo@gem.stack.urc.tue.nl (Angelo Wentzler)
Organization: MCGV Stack, Eindhoven University of Technology, the Netherlands
Subject: Re: CONWAY'S GAME "LIFE" - SOFTWARE?
Message-Id: <2779@tuegate.tue.nl>
Newsgroups: comp.theory.cell-automata
References: <1991Dec1.054210.21850@dsd.es.com>
Sender: ca-request@Think.COM
To: ca@Think.COM

The current version of Xlife is 3.0. I received the sources last year, so by
now there will be a v4.0 or something. I WILL NOT SEND SOURCES!!!!
So, got that out first. Now what I really want to say is, that I've been
experimenting with Death, a reversed Life. A parent in Life is a Child in
Death, so to speak.

This brings some problems; some generation in Life can have several different
parents (generations that came before it) or none! (The so called gardens of
eden). My purpose is developing an algorithm that finds some kind of minimal
parent for a given life-pattern.
With minimal I mean the least possible deviation from the original pattern,
the least possible cells, the most compacted pattern possible or even the
one with the least possible parents.
I have found that when a pattern has N live cells, it's parent has at least 
floor(N/3) live cells and at most 3*N live cells. The search area can be
limited to the second neighbourhood. 
But even then just trying all possible patterns is an immense task. I suspect,
however, that it is impossible to make a set of rules (as with the original 
game of life) Because if you think of life and death as functions from patterns
to patterns, life is neither onto nor one-one! So there is no inverse function
for life (which would be death)....
I think the best way to solve this problem is to adapt the life rules slightly
so that there will be an inverse possible...

If there are people willing to break there heads about this, or just talk me
out of it, let me know what you think.

Angelo Wentzler
-- 
angelo@stack.urc.tue.nl (internet)    Eindhoven University of Technology (nl)
--------------------------------------------------------------------------------
What happens when an unstoppable, undeflectable force hits an unmovable,
indestructable object? I don't know. Gives me a headache, I guess.

From cellular-automata-request@Think.COM  Mon Dec  2 10:51:45 1991
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Date: 2 Dec 91 15:02:34 GMT
From: dl2n+@andrew.cmu.edu (Daniel Edward Lovinger)
Organization: Software Development, Carnegie Mellon, Pittsburgh, PA
Subject: Re: CONWAY'S GAME "LIFE" - SOFTWARE?
Message-Id: <YdCYg__00WD5MAcusE@andrew.cmu.edu>
Newsgroups: comp.theory.cell-automata
References: <1991Dec1.054210.21850@dsd.es.com>
Sender: ca-request@Think.COM
To: ca@Think.COM

angelo@gem.stack.urc.tue.nl (Angelo Wentzler) writes:
> The current version of Xlife is 3.0. I received the sources last year, so by
> now there will be a v4.0 or something.

	Pardon me as I kill this rumor (bang). No such thing as 4.0.

> I WILL NOT SEND SOURCES!!!!

	... but they can be gotten from

	export.lcs.mit.edu:/contrib/xlife.tar.Z

      Dan Lovinger     Computing & Communications      Carnegie Mellon U.
    Internet: dl2n+@andrew.cmu.edu   Bitnet: dl2n+%andrew.cmu.edu@carnegie
   "... and in the stillness, they heard the cry of the golden banana ..."
------------------------------------------------------------------------------

From cellular-automata-request@Think.COM  Mon Dec  2 13:51:52 1991
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Date: 2 Dec 91 14:41:36 GMT
From: bokkie@uctvax.uct.ac.za
Organization: University of Cape Town
Subject: Re: CA software for PC
Message-Id: <201210.293a6240@uctvax.uct.ac.za>
Newsgroups: comp.theory.cell-automata
References: <9111202036.AA23749@bunny.gte.com>, <1991Nov25.145233.14597@panix.com>
Sender: ca-request@Think.COM
To: ca@Think.COM

In article <1991Nov25.145233.14597@panix.com>, james@panix.com (James Britt) writes:
>>Could anyone suggest some software for the PC to run CA experiments?
> 
> CA LAB form AutoDesk comes to mind. I haven't used it, butthe demo
> looks good.  I believe it's about $60.00.
> 
> James
> 
I just got a copy of 'TurboLife' for DOS from :

mike%cside1.UUCP@ucthpx.uct.ac.za

This looks very good.  Has all sorts of options
and runs very fast. 

Frank Bokhorst
Dept. of Psychology
Univ. of Cape Town
South Africa

From cellular-automata-request@Think.COM  Mon Dec  2 15:05:21 1991
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Date: Mon, 2 Dec 91 15:09:18 EST
From: leao@buphy.bu.edu (Joao Leao)
Message-Id: <9112022009.AA10638@buphy.bu.edu>
To: leao@bu-conx.bu.edu
Cc: ca@Think.COM
In-Reply-To: bokkie@uctvax.uct.ac.za's message of 2 Dec 91 14:41:36 GMT <201210.293a6240@uctvax.uct.ac.za>
Subject: Thomas Ray Talk at BU


EVOLUTION AND OPTIMIZATION OF DIGITAL ORGANISMS

Speaker:               Thomas S. Ray
                       University of Delaware

Location:              PRB 593
                       1:30 p.m., Tuesday, December 3, 1991


Dr. Ray was featured in the August 27th New York Times article, "Lively
creation blurs definition of life."  He has created a virtual computer,
"Tierra," within which self-replicating computer creatures change
spontaneously over time through evolution. He was recently awarded a prize
by I.B.M. for his contribution to supercomputing.

Dr. Ray will define "artificial life," state of the art and opportunities
in this emerging field, his ongoing research and potential applications in
the information area.

Synthetic organisms have been created based on a computer metaphor of
organic life in which CPU time is the "energy" resource and memory is the
"material" resource.  Mutation generates new forms, and evolution proceeds
by natural selection as different genotypes compete for CPU time and memory
space.

Diverse ecological communities have emerged.  These digital communities
have been used to experimentally examine ecological and evolutionary
processes.

The computational issue is how to design a computer architecture and
operating system that will support the natural evolution of machine code.
Dr. Ray is experimenting with variations on the successful architecture in
order to find a good balance of computational power and evolvability. He
also seeks to develop an analog to genetic engineering, in which
application codes are inserted into the genomes of digital organisms and
evolved to greater optimality or new functionality, using artificial
selection. A more long term objective is to use digital organisms evolving
freely or under artificial selection, as a source of new paradigms for the
programming of massively parallel machines.


Joao Pedro Leao (Artificial Iconoclast and Director of Computer Resources
Artificial Physics Lab * Boston University - Physics Dept. Boston MA 02215)
 	leao@buphy.bu.edu | leao@buphyc.bitnet | BUPHYC::LEAO 
"Well I am sitting here in Tahiti/ I am laying in the sun and sipping a...
...chartreuse tropical drink!/ and I say: I know those Bermuda shorts!..."

From cellular-automata-request@Think.COM  Mon Dec  2 17:51:56 1991
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Date: 2 Dec 91 20:29:24 GMT
From: jb7m+@andrew.cmu.edu (Jon C. R. Bennett)
Organization: Senior, Math/Computer Science, Carnegie Mellon, Pittsburgh, PA
Subject: Xlife (was Re: CONWAY'S GAME "LIFE" - SOFTWARE?)
Message-Id: <MdCdSYS00VpaI5C5JV@andrew.cmu.edu>
Newsgroups: comp.theory.cell-automata
References: <1991Dec1.054210.21850@dsd.es.com>
Sender: ca-request@Think.COM
To: ca@Think.COM


angelo@gem.stack.urc.tue.nl (Angelo Wentzler) writes:
> The current version of Xlife is 3.0. I received the sources last year, so by
> now there will be a v4.0 or something. 

actualy i have been considering making a new release (it will be 3.1 not
4.0 most likely) since i have a few new speed ideas i have been planing on
trying out, which ill probably get to sometime in dec/jan. so i figured i
would ask if anyone has any new patterns that they have not sent to me
before to do that now so that there might be a new patterns for this
release. 

jon

author xlife


p.s. my time at CMU is about up, anyone know any companies that are
looking for an optimizing speed freak programer? :-)

From cellular-automata-request@Think.COM  Fri Dec  6 15:53:27 1991
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Date: 5 Dec 91 18:59:29 GMT
From: inunn@hpb.hwc.ca
Organization: Health and Welfare, Canada
Subject: Re: Thomas Ray Talk at BU
Message-Id: <1991Dec5.145929.137@hpb.hwc.ca>
Newsgroups: comp.theory.cell-automata
References: <201210.293a6240@uctvax.uct.ac.za>, <9112022009.AA10638@buphy.bu.edu>
Sender: ca-request@Think.COM
To: ca@Think.COM

"Natural selection" of digital organisms is ultimately controlled by a biological organism which monitors their evolution.  The really successful organism we
won't even know about - at least not until its too late to pull its plug.

Ian Nunn with disclaimer.

From cellular-automata-request@Think.COM  Mon Dec  9 13:24:36 1991
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From: ECAI92 Vienna Conference Service <ecai92@ai.univie.ac.at>
Message-Id: <199112091821.AA01488@havanna.ai.univie.ac.at>
Subject: *** ECAI92: Second Call For Papers ***
To: ln@frmop11.bitnet, nl-kr@cs.rochester.edu, vision-list@ads.arpa,
        ca@Think.COM, cvnet@yorkvm1.bitnet, lseward@rand-unix.arpa,
        r34334@uqam.bitnet, simulation@ufl.edu
Date: Mon, 9 Dec 91 19:21:04 MET 
X-Mailer: ELM [version 2.3 PL11]


=======================================================================
 2nd CALL FOR PAPERS - ECAI92 - 2nd CALL FOR PAPERS - ECAI92 - VIENNA
=======================================================================

                          2nd CALL FOR PAPERS

     10th European Conference on Artificial Intelligence (ECAI 92)

                   August 3-7, 1992, Vienna, Austria
                                         

DEADLINE FOR SUBMISSION: January 17, 1992

Papers must be received by the Programme Chairperson before January  17,
1992.  Authors  will  be notified of acceptance or rejection by April 1,
1992. Final camera-ready papers must be received by May 15, 1992.

SUBMISSION OF PAPERS

Authors are requested to submit to the Programme Chairperson 5 copies of
papers  written  in  English  in  hardcopy  format  (electronic  and fax
submissions will not be accepted). Submitted papers must be unpublished,
original  work  and  substantially different from papers currently under
review. They must not be submitted elsewhere before  notification  date.
This  restriction  does  not  apply to workshops and similar specialized
presentations with a limited audience.

Papers can be either long papers (completed research: maximum 5000 words
/  10  single-spaced  pages)  or short papers (ongoing research: maximum
2000 words / 4 pages). Each full page of figures counts  as  500  words.
Each  paper  should  contain an abstract (maximum 200 words). A separate
title page should include the  title,  the  name(s)  of  the  author(s),
complete  address(es),  the specification of one of the topics,  and the 
category long or short.  Papers should be printed on  A4  or  8.5" x 11" 
sized  paper  in letter quality print, with 12 point type (10 chars/inch
on typewriter).

Work described in an accepted paper  may  also  be  illustrated  with  a
videotape  or  a  demo.  Special  sessions  will  be scheduled for video
presentations and demos. Authors wishing to show a videotape or  a  demo
should  specify  the duration and the requirements of the videotape/demo
when submitting their paper for review.

TOPICS OF INTEREST

You are invited to submit an original  research  paper  on  any  of  the
following subjects:

- Automated  Reasoning  (e.g.  automatic  programming,  reasoning   with
     uncertainty,   theorem   proving,  constraint  satisfaction,  logic
     programming, search)
- Cognitive  Modeling  (e.g.  models  for  human  problem  solving   and
     information  processing,  memory  models, computational theories in
     psychology)
- Connectionist and PDP Models for AI (e.g. connectionist architectures,
     connectionist learning, neural networks applications)
- Distributed  AI  and  Multiagent  Systems  (e.g.  distributed  problem
     solving,    distributed    resource    allocation,   communication,
     cooperation)
- Enabling  Technology  and  Systems  (e.g.  machine  architectures,  AI
     computer languages, tools for AI system development)
- Integrated Systems (e.g. integrating several AI  components,  embedded
     AI, integrating AI and conventional systems)
- Knowledge Representation (e.g. terminological knowledge,  nonmonotonic
     logic,  foundations  of  temporal,  causal  and  spatial reasoning,
     abduction, common sense, complexity of reasoning)
- Machine  Learning  (e.g.  inductive  learning,   knowledge   intensive
     learning, discovery, concept formation)
- Natural Language  (e.g.  text  generation  and  understanding,  speech
     understanding, syntax, semantics, discourse, representation issues,
     NL system architecture)
- Philosophical Foundations (e.g. philosophy of mind, functionalism  and
     AI, epistemological foundations)
- Planning, Scheduling, and Reasoning about Actions (e.g.  temporal  and
     causal  reasoning  for planning, task scheduling, plan recognition,
     resource allocation)
- Principles of  AI  Applications  (e.g.  generic  applications,  expert
     system  design, tutoring systems, knowledge acquisition, case-based
     reasoning)
- Reasoning  about  Physical   Systems   (e.g.   modeling,   model-based
     simulation,  qualitative  reasoning, diagnosis, design, monitoring,
     applications  of  causal,  temporal  and  spatial   reasoning   for
     engineering, scientific, medical, economic problems)
- Robotics (e.g. connecting perception to action, sensor-motor  systems,
     kinematics, navigation, grasping)
- Social, Economic, Legal, and Artistic Implications (e.g. AI scenarios,
     ethical issues, legal issues and responsibility, AI and music)
- User  Interfaces  (e.g.  intelligent  graphical  interfaces,   natural
     language  front  ends,  user  models,  knowledge-based  information
     presentation, artificial reality)
- Verification, Validation  &  Test  of  Knowledge-Based  Systems  (e.g.
     improving and securing consistency, completeness, reliability)
- Vision  and  Signal  Understanding  (e.g.  vision  and  perception  in
     biological    and   technical   systems,   sensor   interpretation,
     intelligent signal interpretation).
                                            
PROGRAMME CHAIRPERSON

Papers, workshop proposals and all  inquiries  regarding  the  programme
should be sent to the Programme Chairperson:
   Prof. Bernd Neumann
   FB Informatik
   University of Hamburg
   Bodenstedtstr.16
   D-W-2000 Hamburg 50
   Germany
   Tel: +49(40)4123-6130
   Fax: +49(40)4123-6530
   Email: neumann@rz.informatik.uni-hamburg.dbp.de

THE CONFERENCE

The  European  Conference  on  Artificial  Intelligence  (ECAI)  is  the
European  forum for scientific exchange and presentation of AI research.
The aim of the conference is to cover all aspects of AI research and  to
bring  together  basic  research  and  applied  research.  The Technical
Programme will  include  paper  presentations,  invited  talks,  panels,
workshops,  and  tutorials.  The  conference  is  designed  to cover all
subfields of AI, including non-symbolic methods.

ECAIs are held in alternate years and  are  organized  by  the  European
Coordinating  Committee  for  Artificial  Intelligence (ECCAI). The 10th
ECAI in 1992 will be hosted  by  the  Austrian  Society  for  Artificial
Intelligence  (OGAI).  The  conference  will  take  place  at the Vienna
University of Economics and Business Administration.

PROGRAMME STRUCTURE

Mon-Tue (Aug 3-4): Tutorials and Workshops
Wed-Fri (Aug 5-7): Invited Talks, Paper Presentations, Survey Sessions
Tue-Fri (Aug 4-7): Industrial Exhibition

CONFERENCE FEES

(in Austrian Schillings, approx. 14 AS = 1 ECU, 12 AS = 1 US$)
                                                                        
                                           early       late     on-site
Members of ECCAI member organizations      4.500,-    5.000,-    6.000,-
Non-Members                                5.000,-    6.000,-    7.000,-
Students                                   1.500,-    2.000,-    2.500,-
                            

HELP US TO KEEP YOU INFORMED

Fill out the attached form and return it to our conference office:
   ADV
   c/o ECAI92
   Trattnerhof 2
   A-1010 Vienna
   Austria
   Tel: +43(1)5330913-74, Fax: +43(1)5330913-77, Telex: 75311178 adv a

or by email to: ecai92@ai.univie.ac.at
                 
------------------------------------------------------------------------
------------------ ECAI92 Conference Information Form ------------------

Yes, please send further information about the 10th European Conference
on Artificial Intelligence (ECAI92).

Name:    ________________________________________________________
Address: ________________________________________________________
         ________________________________________________________
         ________________________________________________________
         ________________________________________________________
         ________________________________________________________

I am a member of the following ECCAI member organization:
   o  AEPIA (ES)           o  BAAI (BE)            o  NJSZT (HU)
   o  AFCET (FR)           o  BAIA (BG)            o  NVKI (NL)
   o  AFIA (FR)            o  CSC (CS)             o  OGAI (AT)
   o  AIAI (IE)            o  DAIS (DK)            o  SAIS (SE)
   o  AIIA (IT)            o  FAIS (FI)            o  SCAI (SU)
   o  AISB (UK)            o  GI (DE)              o  SGAICO (CH)
   o  APPIA (PT)           o  IAAI (IL)            o  SKS (CS)
   o  ARC (FR)             o  NAIS (NO)            o  YUGAI (YU)
                                                   o  none

Date: ________________   Signature: _____________________________

------------------------------------------------------------------------

From cellular-automata-request@Think.COM  Mon Dec  9 14:21:02 1991
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Date: Mon, 9 Dec 91 13:19:37 MEX
From: mcintosh@uapnx1.dgsca.unam.mx (Harold V. McIntosh)
Message-Id: <9112091919.AA00471@ uapnx1.dgsca.unam.mx >
To: ca@Think.COM

A recent inquiry (John Bates, <J_BATES@UNHH.UNH.EDU>, Fri, 22 November 
1991 14:39:47) solicits information regarding (3,1) linear cellular 
automata. 

The book [Stephen Wolfram (Editor), Theory and Applications of Cellular 
Automata, World Scientific, Singapore, 1986] may contain the only 
studies ever published about such a topic. Appendices contain 
evolutionary samples from all of the 256 (2,1) automata, at least up to 
to symmetry classes differing by reflection and complementation. As a 
reprint volume, it includes the articles where he originally surveyed 
one dimensional automata, and consequently includes many tables of 
their properties and characteristics. 

When that work was first done, even looking at all of the binary 
automata represented quite an adventure, so it is not surprising that 
little more than browsing was done with other automata, or that a 
restriction to such things as totalistic rules was made. There are far 
too many automata to have looked at all of them individually. 

Mainly noteworthy for its introduction of four classes, [Stephen 
Wolfram, ``Universality and Complexity in Cellular Automata,'' Physica 
D 10 1-35 (1984)], reprinted in the book, surveyed several automata, 
including totalistic (2,2), (3,1), and (5,1) automata. Here he 
encountered examples of the fourth class, which do not exist for (2,1) 
automata and is rare for others. Random totalistic automata are a much 
more fertile source of class iv than arbitrary automata. 

The topic was taken up in popular magazines; for example [A. K. 
Dewdney, ``Computer Recreations - Building computers in one dimension 
sheds light on irreducible complicated phenomona,'' Scientific 
American, May, 1985 (pp. 10-16)], reprinted in [A. K. Dewdney, ``The 
Armchair Universe,'' W. H. Freeman and Company, New York, 1988. ISBN 
0-7167-1939-8]. It reports on several 1-d automata, including Wolfram's 
(3,1) #357. Wolfram wrote a supplement called ``Glider Gun Guidelines'' 
which touched on various automata having glider guns; it may possibly 
still be available (the book shows an address). 

That supplement offered several class iv automata for readers to study, 
together with the declaration that interesting discoveries which were 
sent in might be collected and published. If so, we are not aware as to 
where that may have taken place. 

It is said that he who has a new hammer finds himself surrounded by 
nails; Wolfram's weapon seems to have been Stephen Smale's ``strange 
attractors,'' and a lot of automata came in for a pounding. Still, 
there are other approaches to automata theory, which would affect 
whether or not it would be profitable to study trinary automata. 

As with (2,3/2) or (2,2) automata, the number of (3,1) automata is 
large but not overwhelming; someone might want to try cataloguing them. 
Enumerated or not, they show some interesting features not present in 
the (2,1) automata of Wolfram's appendices. 

Membranes and macrocells are evident in trinary automata, as Wolfram 
observed. They are also present in (2,1) automata, but not evident 
unless one knows to look for them; all can be explained by de Bruijn 
diagrams. 

There are a few trinary class iv automata; Wolfram found the totalistic 
ones, but there are surely a few more. 

Some marginally non-trivial composites are possible, such as 
subautomata and factor automata, but trinary is not complex enough 
to build up direct products or produce Fredkin-type reversibility. 

Nevertheless, there are non-trivial reversible trinary automata; by 
trivial one discounts such things as shifting, permuting, or static 
automata. 

A binary counter is barely possible, but a carry generator seems hard 
to include. Constructing counters is useful to establish the existence 
of configurations of very long period, although that is not the only 
way that long periods can arise. 

Just as interesting Turing machines can be designed to check 
parentheses, search for a mark, and the like, it is possible to 
construct special purpose automata which will perform various tasks. 
However, the essence of Turing machine theory lies in being able to 
construct a universal machine and then show its limitations; this 
requires a certain minimal state-symbol product (albeit it unknown 
just how small). 

Linear (one-dimensional) automata can emulate Turing machines, so in 
principle there is an automaton which can do anything that a Turing 
machine can do; so far this has required a modest number of states per 
cell, although neighborhoods as small as two cells can be used. So one 
could look for a minimal k*r product among (k,r) automata, but there is 
some legitimate doubt that both k and r would both end up as small as 
2 or 3. 

We do not know how familiar Wolfram was with such results while making 
his surveys, although he certainly included conjectures about 
computability in his classifications. Moreover, considerable literature 
exists treating the computability of membership in a Wolfram class. 

One might also insist that there is a difference between saying that 
``an automaton is performing a computation'' and saying that ``we 
cannot determine whether this automaton will perform a certain action.'' 
This objection refers to saying that an automaton is ``performing a 
universal computation'' when we really mean that we can't figure out 
what it is going to do. 

Persons who still want to concentrate on trinary automata will find 
computer programs are not hard to write, but many programs which are 
circulating (such as Rudy Rucker's CA Lab) already include them in their 
repertoire. The proceedings of the conference CA89 [Howard Gutowitz 
(Editor), Cellular Automata: Theory and Experiment, North Holland, 
Amsterdam (Special Volume of Physica D 45 (1990)). Softcover edition: 
MIT Press, Cambridge, 1991 (ISBN 0-262-57086-6)] contain much 
information about automata. Appendix I [David Hiebler, A Brief Review 
of Cellular Automata Packages] describes several programs and how to 
acquire them. 

In particular, the program LCAU31 calculates: evolution, mean field and 
block probabilities, de Bruijn diagrams, ancestors, and sundry tidbits 
of information for (3,1) automata; send inquiries to 

		Harold V. McIntosh
		Universidad Autonoma de Puebla
		Apartado Postal 461 
		(72000) Puebla, Puebla, MEXICO. 

Since (3,1) probability contours are still representable in two 
dimensions, the probability plots are reasonably artistic, but require 
at least CGA; otherwise a PC (clone) with MSDOS suffices. 
--
H. V. McIntosh
Internet: mcintosh@uapnx1.dgsca.unam.mx (through Aug 92)
BITNET: MCINTOSH@UNAMVM1

From cellular-automata-request@Think.COM  Thu Dec 12 09:12:20 1991
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Date: 10 Dec 91 11:52:02 GMT
From: bokkie@uctvax.uct.ac.za
Organization: University of Cape Town
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Herewith a summary of responses to my query about software 
for Conway's game 'LIFE'.  For IBM DOS I have tried TurboLife
and recommend it because it can work with a variety of rules
other than Conway's original.

**********
V. Bauchau:
VINCENT@BUCLLN11.BITNET

For the Macintosh, there a really good PD program called LazLife, by Larry
Hutchinson. I like it very much. It is very fast, and has many options.
Other programs for the Mac are LifeMaker and LifeLab, which, as
far as I know, can also simulate other CA than LIFE.

***********
Simon Klyne:
SIMON@OHM.YORK.AC.UK

If you have Xwindows then there is xlife on the mit anon ftp site
I have an old version which I could mail you if you want
(He adds that the file is about 1Mb)

************
Mike Morris:
MIKE@CSIDE1.UUCP    | ...!uunet!ddsw1!olsa99!oct!cside1!mike

(Sent me a uuencoded PKZIPed file with TurboLife for IBM DOS.
 This program I find very good, but note: it doesn't 
 work with Hercules graphics.)
 
***************
Keith Robinson:
ROBINSON@NUCLEUS.HARVARD.EDU

If you have access to ancient IBM PC shareware libraries,  look 
for a program called "Four". This is a four-colour version of 
life written by my brother (if you find Four, I think there is 
a two-colour version he wrote also, but I forget the name).

From cellular-automata-request@Think.COM  Thu Dec 12 20:11:38 1991
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unsubscribe me

Thanks

From cellular-automata-request@Think.COM  Sat Dec 14 18:14:28 1991
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Date: Tue, 10 Dec 91 19:11:00 GMT
From: robertc@sco.COM (Robert Chansky)
Organization: The Santa Cruz Operation, Inc.
Subject: Re: Thomas Ray Talk at BU
Message-Id: <1991Dec10.191100.10520@sco.COM>
Newsgroups: comp.theory.cell-automata
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In article <1991Dec5.145929.137@hpb.hwc.ca> inunn@hpb.hwc.ca writes:
>"Natural selection" of digital organisms is ultimately controlled by a biological organism which monitors their evolution.  The really successful organism we
>won't even know about - at least not until its too late to pull its plug.
>
>Ian Nunn with disclaimer.


	There was a letter similar to this one in Science News.  Of course,
there is a point here -- if we really do come up with something intelligent
we will have to safeguard it.  But Thomas Ray's organisms can't escape their
very specialized environment.  A virtual computer executes their
instructions, and the 'creatures' cannot exist without it; as Tierra is
constructed, there is no way for them even to perceive the outside world.
This would be equivalent to the bad guys in some video game escaping the
screen, heading over to your bank and taking all of your quarters directly.

	Now, if there were some bug in Ray's code that accidentally allowed a
creature to translate itself to the native code of the machine (say, 386
machine language), and make itself into an executeable file in the operating
system -- and if the creature was smart enough to deduce how to program
itself in 386 native code, and execute itself...  this obviously presents
a danger.  Undoubtedly once Ray's method of evolutionary programming becomes
well known, it will be used to generate antisocial programs, with full
knowledge of the danger.  As always, it is people, not their tools, which
are the problem here.

	It may be possible, though, to generate programs to watch for just such
dangers, and intercept them before they can do much harm.

-- 

                                 . 
                     (.signature at 50 meters)

From hiebeler@Think.COM  Fri Dec 20 14:02:28 1991
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To: ca@Think.COM
Subject: CAM-PC


  I had meant to send this out a long time ago, but it got buried in
my "non-urgent" mail for a while.

  You can write to "campc@automatrix.com" for more information.  Also,
I was just talking to one of the people at Automatrix recently, and
apparently they have added another event counter to CAM-PC.  (I
believe that feature has not been "officially announced" yet, but
should be available soon).



NEWS RELEASE

AUTOMATRIX, INC. INTRODUCES WORLD'S FIRST SINGLE-BOARD, 24-MIPS 
CELLULAR AUTOMATA MACHINE FOR UNDER $2000

REXFORD, NY, October 1, 1991 -- Automatrix, Inc., today announced 
the availability of the full production version of CAM-PC: the first, 
single-board cellular automata machine (CAM) for under $2000.  Though 
a small number of CAMs of various architectures exist in research 
laboratories around the world, CAM-PC is the first, mass-produced 
machine that installs in a standard platform. Designed as an add-in 
board for IBM and compatible personal computers (PCs), CAM-PC will 
easily perform simulations at speeds previously requiring expensive, 
high-end workstations and supercomputers.  

CAM-PC comes with a complete operating and development environment 
and instructional textbook.  In addition to dozens of fully debugged 
experiments which can be used for demonstrations or programming examples, 
specially created software greatly simplifies the task of writing 
custom programs.  No longer are cellular automata animations the exclusive 
domain of those fortunate enough to work with only the fastest computers.  
CAM-PC and its powerful graphics will bring the universe of animated 
cellular automata to everyone with a standard PC.

Cellular automata have a surprisingly wide range of applications.
They have been used to simulate many physical phenomena and have been
most studied as lattice-gas models of fluids. They are also
particularly well-suited to applications in materials science,
statistical mechanics, diffusion and dispersion, granular flow and
phase transitions.  Cellular automata have also found use outside of
the physical sciences, including applications in signal processing,
radar target tracking, economic modeling, virus spreading and
distributions, optimization problems, performance modeling of parallel
computer architectures and artificial life. For researchers and
educators in these and many other areas, CAM-PC will be an invaluable
tool.

CAM-PC is conceptually different from any other computational 
device in its price range.  Traditionally, problems have been solved 
by arranging a model in a computer's memory and then processing pieces 
of the model with long instruction sequences. This is inefficient 
and expensive for many complex calculations.  Fortunately, it is no 
longer necessary.

With a CAM, problems are solved by arranging a model in memory and
processing the entire model with simple RISC-like instructions.  This
works like a single-instruction multiple-data (SIMD) parallel
processor, such as the CM-2 from Thinking Machines Corporation.  With
this approach, all of the computer's resources are efficiently brought
to bear on the problem, greatly reducing computational times.

CAM-PC achieves its phenomenal 24 MIPS performance by parallel
processing and overlapping operations. "It performs both a gather
operation and a transform operation on two processors in a single
clock cycle" explains Mukesh Chatter, the lead engineer of the product
design team.

CAM-PC's integrated graphics is specially designed for CA animations.
A movie is easier to understand by watching it run than by viewing the
frames individually.  In the same way, complicated, non-linear
dynamical systems are much easier to understand if calculations for
their simulations are graphically displayed as they evolve in real
time.  Explains David Cross, VP Application Software, "Unfortunately
most conventional computers can't display the results of complicated
calculations as [rapidly as] they occur.  Users were faced with the
choice of using either crude animations or very expensive graphics
hardware.  CAM-PC now provides a third alternative."  Because CAM-PC
is tightly coupled to its associated graphics display, the user can
observe cellular automata simulations in real time, as programs run
and calculations occur.  The advantages of combining cellular
automata, RISC-SIMD processing, and real-time visualization are
obvious and have lead to the creation of a powerful new tool for
interactive experimentation: CAM-PC.

CAM-PC displays 65,536 cells on an ordinary TTL color monitor in 2
dimensions, arrayed 256 across and 256 down.  Cell states are mapped
as different colors under user control. Programs are stored in eight
64K-bit lookup tables for instantaneous processing.  The whole array
is scanned, displayed, and updated 60 times/sec. The result is a
smooth animation that brings the real-time computations to life.

CAM-PC is implemented on a full-length PC/XT board with over 60
low-power IC's, including 20 custom programmed parts.  Because CAM-PC
does most of the work, the board and its software operate in the
oldest and newest PC's with little difference in performance.

The programmable components are a unique feature of CAM-PC which allow
future enhancements through firmware upgrades.  This design strategy
has already proven its value. CAM-PC was originally released in
December 1990 to selected beta sites, and with firmware upgrades, all
of these sites have the latest circuit enhancements.

A CAM-PC program consists of a sequence of rules and models, or
patterns, that are loaded into CAM-PC at predetermined time intervals.
The rules are applied to the patterns as the program runs.  The
user may start, stop, retard, accelerate, or reverse the program, or
make changes in the rules and patterns at any time during its
operation.

In addition to ordinary "cellular automata neighbors", CAM-PC
rules can use inputs from temporal phase bits", spatial
parity bits" and a variety of additional inputs, including other
CAM-PC boards or user-supplied logic. CAM-PC is also the first machine
to implement Margolus neighborhoods directly in hardware.

Extensive gluing logic incorporated in CAM-PC allows multiprocessing 
with several boards.  Up to four can be combined in a single PC, and 
with an appropriate expansion bus, even more may be added.  Thus, 
large models are easily accommodated.  Horizontal and vertical gluing 
allow spatial extension and depth gluing provides additional bits 
per cell.  CAM-PC's design offers the user maximum flexibility.

CAM-PC is available by mail order from Automatrix, Inc.  The complete
CAM-PC Package, including hardware, software, documentation and the
book "Cellular Automata Machines: A New Environment for Modeling," by
Toffoli and Margolus, sells for $1950.  Payment may be made by check
or money order, or by purchase order from "Fortune 1000" companies,
U.S. Government laboratories and accredited educational institutions.
With a current delivery of 2 to 4 weeks, CAM-PC makes animated,
interactive experimentation an affordable, easily obtainable option
for everyone.

For more information or to place an order, write to: CAM-PC, 
Automatrix, Inc., P.O. Box 196, Rexford, NY 12148-0196 or call the 
sales department at: +1 (518) 877-7270.

---
CAM-PC is a trademark of Automatrix, Inc.  IBM PC and PC/XT are trademarks 
of International Business Machines Corporation. CM-2 is a trademark 
of Thinking Machines Corporation.


--
Dave Hiebeler                  | Internet: hiebeler@think.com
Thinking Machines Corporation  | UUCP: {uunet,harvard}!think!hiebeler
245 First Street               | Bitnet: hiebeler%think.com@mitvma.bitnet
Cambridge, MA 02142  USA       | Phone:  (617) 234-4070 (work)

