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From: smoliar@vaxa.isi.edu (Stephen Smoliar)
Newsgroups: comp.ai.philosophy
Subject: Re: Chinese Room Experiment: empirical tests
Keywords: Adaptation, Convergence
Message-ID: <15812@venera.isi.edu>
Date: 27 Nov 90 16:27:27 GMT
References: <7852@uwm.edu> <15799@venera.isi.edu> <7890@uwm.edu>
Sender: news@isi.edu
Reply-To: smoliar@vaxa.isi.edu (Stephen Smoliar)
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In article <7890@uwm.edu> markh@csd4.csd.uwm.edu (Mark William Hopkins) writes:
>In article <15799@venera.isi.edu> smoliar@vaxa.isi.edu (Stephen Smoliar)
>writes:
>
>(The experiment was):
>>>The concept is real simple.  Try to learn a new language by imitation.
>...
>>>So here's what you should do: take out about 10 books written in a language
>>>you don't understand (like 10 books written in Spanish)... Rewrite the exact
>>>contents of each book.
>
>>I noticed that the first reaction to this proposal was one of self-righteous
>>skepticism.  Unfortunately, it is very hard to deal with this situation with
>>anything other than anecdotal evidence.  Having said that, let me throw out
>>two such anecdotes.
>
>Both of your anecdotes actually relate to a general situation that you might
>call learning-by-imitation, which bears an obvious relation to the ancient
>method of learning-by-apprenticeship.
>
>It seems to me that this is by far the most natural and most efficient way for
>a human being to learn new information and to accquire new skills and new
>expertise.  It's also obviously the oldest method, since it's the only one
>that
>doesn't require formal schooling or reading and writing.
>
>Symbolic architectures can only incorporate this desireable feature in a
>roundabout way ... because they're not explicitly designed to adapt over
>time.  On the other hand, the ability for the system to adapt itself to the
>regularities of its environment is something that almost characterises
>connectionist learning architectures (like backpropagation).
>
Now that the propaganda ploy has been revealed, perhaps we can try and sort out
just what issues are at stake.  Of the above three paragraphs, I agree entirely
with the first two.  The third, however, gives me pause.  My own feeling is
that BOTH symbolic and connectionist architectures may be laboring under the
illusion that one may implement some sort of direct path to
learning-by-apprenticeship.  By using the word "illusion,"
I hope to have conveyed the opinion that such a direct path
may not be particularly feasible.  My current feeling is that
Gerald Edelman's recent work on a "biological theory of consciousness"
(THE REMEMBERED PRESENT) might provide a better approach to how such a
goal may eventually be attained.  Let me try to outline my interpretation
of his story.

Edelman's basic approach is that the ability to form perceptual categories lies
at the heart of all our cognitive behavior.  Furthermore, it is important that
such an ability develop in the absence of any A PRIORI terminology which would
basically serve as "hints" about what categories to look for.  This is his
fundamental beef against advocates of symbolic architectures:  You're garden
variety scene analysis system on a symbolic architecture is helpless without
a knowledge base which endows it with some sort of "world model."
Connectionist architectures, on the other hand, do not require such
A PRIORI terminology.  (See "Feature Discovery by Competitive Learning"
by Rumelhart and Zipser--Chapter 5 of the "PDP Bible"-- for a nice
demonstration of this claim.)

However, there is much more to Edelman's story than perceptual categorization.
Most important is that his whole story about memory is one of REcategorization.
Categories are not static.  They are constantly being revised with every new
stimulus that comes along.  As Oliver Sacks recently pointed out in his NEW
YORK REVIEW article on this subject, a fundamental difference between computers
and people is that computer memories retrieve the same thing each time they are
probed, while people are far more fallible (which, as Sacks points out, is less
of a bug and more of a feature when you start getting into more advanced forms
of behavior).  This is where Edelman begins to depart from the connectionists,
since convergence is not one of his objectives.  His argument is that if one
wishes to build a "conscious machine" (and let us assume that such
consciousness is necessary for such behavior as learning-by-apprenticeship),
that machine had better be VERY dynamic, even at the level of something such
as memory which we tend to think must be relatively static.

If you are going to deal with a system which is always in flux, the next thing
you are going to need is a way to deal with time.  In other words this dynamic
system must deal with the fact that it resides in a dynamic world.  Another way
of putting it is that you are going to need some kind of machinery which can
sort out those system dynamics concerned with stimuli of the present from those
based on stimuli of the past, as well as motor control hardware which can plan
actions for the future.  Edelman argues that the brain has such hardware in the
hippocampus, the cerebellum, and the basal ganglia.

At this point you can gingerly start to approach questions of learning.  With
all those dynamics, "concepts" cannot be expected to be implemented in the
clean logical forms of symbolic knowledge bases.  Rather, they may be regarded
as a recursive layer of categorization--categories of the patterns of behavior
arising from the dynamics of the system described thus far.  Actually, there
will be categories for both what our intuition would call concepts and
RELATIONS between those concepts.  Such categories ultimately will entail
associations between perceived stimuli and recollections of past stimuli,
to the point where we have some level of "imaging" power by which a memory
induces neural activity similar to that triggered by "real" stimuli.  This
brings us to a capability which Edelman calls "primary consciousness."

Note that no symbols have yet entered the picture.  They come in through the
acquisition of linguistic capabilities, which Edelman views as yet another
recursive layer of category formation.  At this stage we begin to associate
LABELS with out memories.  The labels, themselves, then assume the role of
new categories;  and relations among those categories bring us to the structure
of language.  Only after all these layers are in place are we in a position to
"reason" with them, i.e. use them to expand our view of the world and our
associated "mental state."  This is the point at which we are doing learning,
and we are using all the machinery outlined in the preceding paragraphs to do
it.

The bottom line, then, is that symbolic architectures definitely have critical
shortcomings;  but connectionist learning architectures which throw so much
weight on convergence are probably no better off.  We are too interested in
building some sort of transducer with predictable input-output behavior than
a dynamic system constantly reconfiguring itself as a result of its exposure
to a changing world.  Needless to say, building such a system is intimidating,
to say the least.  Therefore, we should take some comfort in the fact that
Edelman and his colleagues have already begun to build working simulations
of the first stages of his model.  Such simulations may point the way to
systems capable of such skills as learning-by-apprenticeship.

>Another part of the experiment relates to a situation (which will eventually
>occur) where you can actually become fluent or knowledgeable in an area
>(particularily in a new language) without actually having the slightest idea
>of what it is you're saying or doing (or why it works).
>
This can happen quite frequently when you learn by imitation.  I would also
argue that one of the reasons it happens in that imitation requires that the
BODY learn.  In other words we cannot take a dualist view which divorces mind
from body.  The WHOLE SYSTEM is what is doing the learning;  and often the body
gets involved in the "rhythm" or "ritual" of a situation, guiding behavior to
those actions which are appropriate to solving a given problem or making an
appropriate decision.

=========================================================================

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"It's only words . . . unless they're true."--David Mamet