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From: sosic@kurango.cit.gu.edu.au (Rok Sosic)
Subject: Re: Kinetic CA
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Date: Tue, 25 Apr 1995 23:31:30 GMT
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Xref: glinda.oz.cs.cmu.edu comp.theory.cell-automata:3533 comp.ai.alife:3154

"Joseph J. Strout" <strout@helmholtz> writes:

>On 19 Apr 1995, Tihamer Toth-Fejel wrote:

>> When Von Neumann started working on robotic self-replication, he first
>> tried the "robot in a warehouse of spare-parts" approach, otherwise
>> known as the kinematic approach.   But it was was mathematically too
>> unweildy, so he invented CA.  I wonder if there has been any serious
>> theoretical work making CA more kinetic.

>Last year I developed a simulation I called "Biomatrix" which sounds 
>similar to what you're asking about.  Cells in the matrix could have a 
>variety of states, divided into three general categories: empty, 
>structural unit, or instruction.  Cells could also contain a "program 

You might want to have a look at our paper:
	R. Sosic and Robert R. Johnson. Computational Properties of 
	Self-Reproducing Growing Automata. (to appear in BioSystems)

The paper is available from:
	http://www.cit.gu.edu.au/~sosic/living.html
	ftp://ftp.cit.gu.edu.au/pub/R.Sosic/biosystems95.ps.Z

Abstract 

Living organisms perform much better than computers at solving complex, 
irregular computational tasks, like search and adaptation. Key features 
of living organisms, identified in the manuscript as a basis for their 
success in solving complex problems, are: self-reproduction of cells, 
flexible framework, and modification. These key features of living 
organisms are abstracted into a computational model, called Growing 
Automata. Growing automata are suited for extremely large computational 
problems, such as search problems. 

Growing automata are representatives of soft machines. Soft machines 
can change their physical structure as opposed to hard machines which 
have fixed structure. An example of a soft machine is a living organism, 
an example of a hard machine is an electronic computer. The computational 
properties of soft and hard machines are analyzed and compared. An analysis 
of growing automata demonstrates their advantages, as well as their 
limitations as compared to hard machines. 

Cheers,
Rok
--
Rok Sosic (sosic@cit.gu.edu.au)                     _--_|\
School of Computing & Information Technology       /      GU
Griffith University, Nathan, QLD 4111, AUSTRALIA   \_.--._/
phone: +61 7 875 5026; fax: + 61 7 875 5051              v
WWW: http://www.cit.gu.edu.au/~sosic/index.html

