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Article 7085 of comp.ai.philosophy:
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>From: bill@nsma.arizona.edu (Bill Skaggs)
Newsgroups: comp.ai.philosophy
Subject: Re: self-evolution
Message-ID: <BILL.92Oct1165428@ca3.nsma.arizona.edu>
Date: 1 Oct 92 23:54:28 GMT
References: <92274.201057GE0QC@CUNYVM.BITNET>
Sender: news@organpipe.uug.arizona.edu
Organization: ARL Division of Neural Systems, Memory and Aging, University of
	Arizona
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In-Reply-To: GE0QC@CUNYVM.BITNET's message of 1 Oct 92 00: 10:57 GMT

GE0QC@CUNYVM.BITNET (Levi) writes [edited for spelling and clarity]:

   > . . . the major difference between a human brain and a computer
   > is that a computer will be able to self-evolve.  If a computer
   > is convinced that a change in its algorithm would enhance its
   > capabilities all it has to do is change its algorithm.

I think the question of self-evolution is very interesting.  Of course
humans as well as computers can change their algorithms to enhance
their capabilities -- that's why we go to school.  But there is a
level, the neural level, at which our algorithms seem to be fixed, or
at least insulated from consciousness.  Does the same thing
necessarily apply to computers?

Hofstadter, for one, argues that it does (in GEB).  He says that
flexibility must always be built upon a fixed substrate -- that every
functional system has *some* level insulated from control by higher
levels.  The argument seems plausible to me:  it's hard to see how a
system could intelligently change itself at the most fundamental
level.  A system surely could not predict the effect of such a change
in its own structure, so it would essentially be a random mutation --
and random mutations, in the absence of a selection mechanism, lead
only to chaotic instability.  

But this isn't exactly a mathematical proof, and I still have a
smidgen of doubt.

	-- Bill


