Path: utzoo!news-server.csri.toronto.edu!rutgers!bellcore!uunet!karln!karln!karln
From: karln@uunet.uu.net
Newsgroups: comp.ai
Subject: Re: Discover magazine's "Invasion of the Insect Robots"
Message-ID: <1991Mar12.195915.673@uunet.uu.net>
Date: 12 Mar 91 19:59:15 GMT
References: <92995@lll-winken.LLNL.GOV>
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Organization: Sam76 - Pennington NJ
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In article <92995@lll-winken.LLNL.GOV> loren@tristan.llnl.gov (Loren Petrich) writes:
>flak from those who have worked in the symbolic-AI field, who have
>accused him of scaling down his goals from human-level intelligence to
>insect-level intelligence.
>
	I was at the pub the other night, after which I am not sure
there is a difference[;-}> <-A sly sort of smile from a square head with beard.

  Very interesting subject. Although I have heard repeated claims that neural
nets are supposed to learn, as in the learning to walk example, this is the 
first I personally have heard of such success. It seemed to me that Neural
Nets were mostly only good for Statistical output, in other words, given a 
number in, the Neural Nets Statistics 'Database' shows that this is probably
the number out. This is from seeing many Cartesian to Polor converters and 
such.

   I suppose what is involved in a neural net learning to walk is a "Feels 
good" circut or subroutine for feedback. If the bug is not moving, the neural
net gets negative feedback. If the bug is moving, then the net gets positive
feedback. The level or severity of feedback would depend on haw well the bug is
moving as told. If the "Barin" wants to go foward, but the neural net drives
the bug slightly sideways, then the feedback is bad. The feedback gets better
as the bug goes straighter, and worse as the bug goes more sideways. I wonder
what other type of feedback is required to get the business working properly.
Do all the legs current positions need to be feedback? How about the current
leg positioning command? This seems like something to keep track of around here.


Karl Nicholas
karln!karln@uunet.uu.net