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From: rstevew@armory.com (Richard Steven Walz)
Subject: Re: Training sets
Organization: The Armory
Date: Sun, 18 Dec 1994 11:58:28 GMT
Message-ID: <D1099H.6qH@armory.com>
References: <165@leopold.win-uk.net> <D0LzEF.B2@wave.scar.utoronto.ca>
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In article <D0LzEF.B2@wave.scar.utoronto.ca>,
FUNK  STEVEN LESLIE,,Student Account <93funkst@wave.scar.utoronto.ca> wrote:
>Hi,
>
>	I've noticed the same problem from a cognitive point of view.  I see and read about a lot of people using multi-layered systems trained with backprop to model cognitive phenomena.  The problem is that a system like this learns the functions in the training set and emulates them.  Which tells you little or nothing about the underlying system at work in the human mind.  There is a greater envolvment of empirical verification in the cognitive arena.  But still the problems do persist.  I would also be 
>
>
>sted in hearing about any standardized tests for network performance.  Not just from a computational point of view, but from a cognitive one as well.
>
>Steve Funk
>93funkst@wave.scar.utoronto.ca
>
---------------------
Might it be that neural net simulations will not tell us so much about
cognitive truth about so-called "human" processes, as those are linked
meta-processes above the level of nnet processing. Example: I don't know
much about how I see shapes, except that there seem to be a bunch of nnets
that react for lines, borders, curves, etc., when then what a cognitive
researcher wishes to know is how do the parts act together to "feel" itself
to be aware and "cognitive"? This process may NOT be nnet oriented. Or the
manner in which it is says little about the process flow! The study of
grey matter is not, after all, the study of personality!
-RSW

