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From: u-jmolse%sunset.utah.edu@wasatch.UUCP (John M. Olsen)
Newsgroups: comp.ai.neural-nets
Subject: Re: NN Question
Message-ID: <1229@wasatch.UUCP>
Date: 3 Mar 89 03:50:36 GMT
References: <32125@gt-cmmsr.GATECH.EDU>
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Reply-To: u-jmolse%sunset.utah.edu.UUCP@wasatch.UUCP (John M. Olsen)
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Organization: University of Utah, Computer Science Dept.
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kirlik@hms3.gatech.edu (Alex Kirlik) writes:
>Why should a net with only a few dozen neural units be
>successful at mimicking human behavior that is presumably
>the result of the activation of a tremendous number of
>neurons?  That is, why should a small number of units
>be successful at simulating the behavior of a large 
>number of neurons?

>A second answer might be that that neural processing has 
>self-similar properties.

>Alex Kirlik  UUCP: kirlik@chmsr.gatech.edu {backbones}!gatech!chmsr!kirlik

I've noticed that many natural things have a self-similar property which
looks quite a bit like what you are talking about.  Just as a very simple 
example, look at some birds flocking as they fly.  Each one is a distinct 
entity, yet they perform flying maneuvers as if they were each part of one 
larger entity.  If you're interested in this, see the ACM SIGGRAPH '87 
conference proceedings, and look up Craig W. Reynolds' paper on "Flocks, 
Herds, and Schools:  A Distributed Behavior Model" where he models how 
critters group as they move.

Just as an off-the-cuff observation, it looks to me like any gathering of
(supposedly) independently behaving things (birds, people, models of 
neurons) can be looked at as a larger entity.  Such an entity could 
actually seem to be less complex than it's parts if they interact in 
just a small number of ways.

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