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From: sticklen@cps.msu.edu (Jon Sticklen)
Newsgroups: comp.ai.philosophy
Subject: Re: Reasoning Paradigms
Message-ID: <1990Oct9.003128.12594@msuinfo.cl.msu.edu>
Date: 9 Oct 90 00:31:28 GMT
References: <JMC.90Oct8083235@Gang-of-Four.usenet>
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Organization: Michigan State University
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From article <JMC.90Oct8083235@Gang-of-Four.usenet>, by jmc@Gang-of-Four.usenet (John McCarthy):
>  ...
> We can make an analogy with the fact that we can write an interpreter
> for any good programming language in any another.  We can talk about
> logic in ordinary language, and we can formalize ordinary language and
> reasoning in logic.

Although we can write an interpreter for any good programming language
in any other, the more salient obsevation is that certain operations
are more easily carried out in particular langauges. Eg, if I want to
maniupulate lists, I am a bit more likely to want to use LISP than
I am to want to use COBOL, although each is a general purpose language.

Even more central is the example that should I want to do a statistics
problem of some sort, I would be yet more likely to select SPSS
as my language of choice. The reason would seem clear - SPSS
gives me exactly the language I want to describe the statistics problem
at hand. The generalization of this line - ie, special purpose languages
allow easier represtatation of problem solving situations *they fit* -
leads in knowledge based systems to the Task Specific Arch schools that
have developed over the last decade. (Eg, Chandrasekaran, McDermott, 
Steels, etc) 

The bottom line may be that although we *could* represent problem solving
with general purpose tools, that it may be much easier to do with
a suite of techniques/tools each tuned for their particular problem
solving situations.

	---jon---