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Article 6224 of comp.ai.philosophy:
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>From: roitblat@uhunix.uhcc.Hawaii.Edu (Herbert Roitblat)
Subject: Re: Re: Transducers
Message-ID: <1992Jun12.022620.22946@news.Hawaii.Edu>
Summary: The distinction is between core vs no core, not computation
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References: <1992Jun10.203412.19158@news.Hawaii.Edu> <4138.708217481@mp.cs.niu.edu>

In article <4138.708217481@mp.cs.niu.edu> rickert@mp.cs.niu.edu (Neil Rickert) wrote:

In article <1992Jun10.203412.19158@news.Hawaii.Edu>
roitblat@uhunix.uhcc.Hawaii.Edu (Herbert Roitblat) writes:

>>     An alternative to the mind/transducer argument suggests that
>>the mind is a central computational core surrounded by storage
>>and peripheral devices.

>  The word "alternative" is at the heart of what I consider to be
>a serious misunderstanding.

>  We are looking at two possibilities:

>	1: The mind is a transducer

>	2: The mind is a set of peripherals connected to a computation
>	   core.

>  So far, so good.  But you and Harnad both point to various points of
>evidence and essentially say "Look at this evidence - it must be a
>transducer.  Possibility 1 is true, so possibility 2 is false."


>  But I believe this is a wrong approach.  We should consider that both
>possibilities could equally be true.  That is, they could both be
>descriptions of the same system.  

If these hypotheses are mutually exclusive then they cannot both be
true simultaneoulsy.  Either the mind has a central computational
core, or it does not.  What you might want to argue is that they both
have heuristic value at different times.  Contrary to what you seem
top be saying, the data do matter.  Freed of the constraints of data,
any description can be attached to any object.  If one uses a
completely irrelevant description as a heuristic base one is very
likely to be misled in both the formulation of research and theory and
in the interpretation of the result.


>  To put this in perspective, consider an automobile.  This doesn't look
>like a set of peripherals and a computational core.  But it can still
>be described that way.  

An automobile is about as far from a computational core device as one
can get.  When one presses on the brake, energy is transferred from
the brake pedal via a series of levers and hydraulic hoses to the
brake shoes or discs.  If the car had a computational core, a signal
would travel from the brake to the core and from the core to the
device.  Attempts to repair a car based on such a computational core
theory would surely end in failure and possibly in death.  


>It doesn't much matter whether the automobile
>physically seems to fit the computational view.  It is still a useful
>view which allows you to ignore details . . .

You can use many different equations to describe the brake function,
but none of them forces an interpretation of the car as computational
core surrounded by peripherals.  Only certain equations can be validly
called descriptions of the brake system.  The facts do matter.  Any
abstraction allows you to ignore at least some of the details.  There
is nothing in the computational core view that licenses one set of
equations over another or allows us to ignore certain details and not
others.  You are arguing for abstraction, not for a computational
core.


>>                                             A major portion of
>>the brain is intimately involved in perception and motor control
>>and these are the same portions that seem to be required for
>>intelligence.  In support of such a claim that perception and
>>motor control are the seats of intelligence, psychological
>>research finds that intelligent performance is often the product
>>of pattern recognition rather than superior computational skill
>>(e.g., de Groot, 1966).

>  I certainly agree that pattern recognition is important.  . . .

> But why does pattern recognition rule out computational skill?

Here you seem to have misunderstood the nature of the claim.  Master
chess players are not necessarily smarter than poorer players, and
they do not appear to employ better search heuristics.  Rather, they
seem to be able to recognize more sensible chess positions than poorer
players recognize and they know what moves have worked in the past in
the presence of those board configurations.  Search heuristics are
computationally very expensive.  If one wanted to MODEL human chess
masters (as opposed to building successful chess-playing programs),
the way to do it would be with improved pattern recognition and
storage algorithms rather than with improved tree-traversing
algorithms.  

>Surely pattern recognition is a computational task of enormous
>complexity.


Surely you are correct.  Nevertheless being committed to computation
does not commit one to a certain computational architecture.  You seem
to conflating computation with the idea of a computational core.  The
idea of mind as transducer implies that the computations are
distributed throughout the system and cannot be concentrated in a
disembodied core onto which the peripherals project their sensory
information. The distinction between the two hypotheses we are
discussing is not between computation versus no computation it is
between core versus no core.


--
Herbert Roitblat                    roitblat@uhunix.uhcc.hawaii.edu
Department of Psychology            roitblat@uhunix.bitnet
University of Hawaii                (808) 956-6727  (808) 956-4700 fax
2430 Campus Road,                   Honolulu, HI 96822 USA


