Path: utzoo!attcan!uunet!husc6!psuvax1!burdvax!sdcrdcf!trwrb!aero!venera.isi.edu!smoliar
From: smoliar@vaxa.isi.edu (Stephen Smoliar)
Newsgroups: comp.ai
Subject: Re: Me and Karl Kluge (no flames, no insults, no abuse)
Summary: There he goes again.
Message-ID: <5669@venera.isi.edu>
Date: 9 Jun 88 04:05:36 GMT
References: <1792@pt.cs.cmu.edu> <1312@crete.cs.glasgow.ac.uk>
Sender: news@venera.isi.edu
Reply-To: smoliar@vaxa.isi.edu.UUCP (Stephen Smoliar)
Organization: USC-Information Sciences Institute
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I see that Gilbert Cockton is still judging the quality of AI by his
statistical survey of bibliographies in AAAI and IJCAI proceedings.
In the hope that the rest of us agree to the speciousness of such arguments,
I shall try to take a more productive approach.
In article <1312@crete.cs.glasgow.ac.uk> gilbert@cs.glasgow.ac.uk (Gilbert
Cockton) writes:
>
>The point I have been making repeatedly is that you cannot study human
>intelligence without studying humans.  John Anderson and his paradigm
>partners and Vision apart, there is a lot of AI research which has
>never been near a human being. Once again, what the hell can a computer
>program tell us about ourselves?  Secondly, what can it tell us that we
>couldn't find out by studying people instead?

Let us consider a specific situation.  When we study a subject like physics,
there is general agreement that a good textbook must include not only an
exposition of fundamental principles but also a few examples of solved
problems.  Why are these examples of benefit to the student?  It would
appear that he uses them as some sort of a model (perhaps the basis for
analogical reasoning) when he starts doing assigned problems;  but how
doesd he know when an example is the right one to draw upon?  The underlying
question is this:  HOW DOES KNOWLEDGE OF SUCCESSFULLY SOLVED PROBLEMS
ENHANCE OUR ABILITY TO SOLVE NEW PROBLEMS?

Now, the question to Mr. Cockton is:  What have all those researchers who
don't spend so much time with computer programs have to tell us?  From what
I have been able to discern, the answer is:  NOT VERY MUCH.  Meanwhile, there
are a variety of AI projects which have begun to address the questions
concerned with what constitutes experiential memory and how it might be
modeled.  I am not claiming they have come up with any answers yet, but
I see no more reason to rail against their attempts than to attack attempts
by those who would not sully their investigative efforts with such ugly
artifacts as computer programs.