Path: utzoo!attcan!utgpu!jarvis.csri.toronto.edu!cs.utexas.edu!swrinde!zaphod.mps.ohio-state.edu!think!ames!haven!udel!princeton!phoenix!eliot
From: eliot@phoenix.Princeton.EDU (Eliot Handelman)
Newsgroups: comp.ai
Subject: Old AI (was: Re: Some Sequence Prediction Work (actually, synthesis of regexprs))
Message-ID: <11988@phoenix.Princeton.EDU>
Date: 6 Dec 89 19:43:31 GMT
References: <11883@phoenix.Princeton.EDU> <5234@bgsuvax.UUCP> <7200@pt.cs.cmu.edu>
Reply-To: eliot@phoenix.Princeton.EDU (Eliot Handelman)
Organization: Princeton University, NJ
Lines: 43

In article <7200@pt.cs.cmu.edu> valdes@b.gp.cs.cmu.edu (Raul Valdes-Perez) writes:
;Simon & Kotovsky wrote a program in an attempt to reproduce human
;ability and shortcomings in sequence-extrapolation tasks.  The 
;justification of this research was:  people arrive at answers on
;such tasks, despite the logical impossibility of a unique answer;
;how can one explain this empirical phenomenon?  Read the paper to
;know how well they did.
;
;Later, Klahr & Wallace wrote a program for the same task, without
;any intent to model human problem-solving, just to have it "work"
;well.
;
;The first reference is "Human acquisition of concepts for sequential 
;patterns," Psychological Review, 70, 534-546.  
;The second is "The development of serial completion strategies:  An
;information-processing analysis," British Journal of Psychology, 61(2), 
;243-257.

I went through Simon & Kotovsky, and it occurred to me that in addition
to the much discussed categories of "strong" and "weak" AI there is actually
a third: "old" AI. The article appeared in 1963: they have a footnote to
the effect that "human thinking processes are essentially list processes."
Thus they have a program which generates sequences given a few rules; they
contend that what happens in the mind must be similar to their program.
Apparently Lisp-like languages (their programs were written in IPL-V, the
language of GPS) were at one time advanced as "languages of thought." There
are corresponding units in the mind that take CARS, CDRS, do RPLACAs, etc.

Why think this way? Because there weren't any other plausible candidates
for the claim that computer programs can model the mind (my reasoning owes 
something to Nietzsche). 

"Old" AI says: the claims of the AI community are supported by the best
programming paradigm available, and vice-versa. This happened, in 1963, to be 
IPL-V, GPS, etc.

No malice intended to Simon and Kotovsky: I'm sure this isn't how they 
saw things. But the lesson of "old" AI is that we, at least, ought to
be able to see through the error: there's no necessary relationship between
these claims and these programming paradigms. The paradigms just happen to be
around; the claims just happen to be around. Ergo these paradigms must 
support these claims. Possibly one could extend this fallacy to paradigms
of thought in general.