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Article 1998 of comp.ai.philosophy:
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>From: weemba@libra.wistar.upenn.edu (Matthew P Wiener)
Newsgroups: comp.ai.philosophy
Subject: Re: Neuron based neural nets
Message-ID: <59688@netnews.upenn.edu>
Date: 9 Dec 91 22:59:18 GMT
References: <3942@papaya.bbn.com> <58114@netnews.upenn.edu> <3949@papaya.bbn.com> <58348@netnews.upenn.edu> <3962@coconut.bbn.com>
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Reply-To: weemba@libra.wistar.upenn.edu (Matthew P Wiener)
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In-reply-to: cbarber@bbn.com (Chris Barber)

In article <3962@coconut.bbn.com>, cbarber@bbn (Chris Barber) writes:
>>So they model feedback via climbing fibers, not chemistry.  Whether
>>this counts as backpropagation per se, I don't know.

>This isn't backpropagation at all. What they seem to be talking about
>here is a kind of feedback loop.

And this is precisely where I hesitate.  Neural nets have a plasticity
of definition, and can simulate each other in various ways.  Is the
Pellionicz & Llinas feedback mathematically inequivalent to all forms
of backpropagation, perhaps in a differently connected net?

Of course, if this hypothetical mathematical boogiemonster is oddball
enough, the backpropagation loses its biological relevance.
-- 
-Matthew P Wiener (weemba@libra.wistar.upenn.edu)


