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From: tjhorton@ai.toronto.EDU ("Timothy J. Horton")
Newsgroups: comp.ai.digest
Subject: Re: Approaches to AI
Summary: research paradigms -- where to from here?
Keywords: research paradigms
Message-ID: <8803062135.AA02549@ai.toronto.edu>
Date: 6 Mar 88 21:35:30 GMT
References: <8803020957.AA14596@ucbvax.Berkeley.EDU>
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Organization: Department of Computer Science, University of Toronto
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jbn@GLACIER.STANFORD.EDU (John B. Nagle) writes (very roughly):
>     McCarthy has recently described two paths to artificial intelligence.
>But his two, while the most active, are not the only ones in which substantial
>work is underway.  A more general taxonomy might be outlined as follows:
>     1.  "Good, old fashioned AI". ... to model the world using formalisms
>	  related to mathematical logic.
>     2.  Neural networks. ... development of massively parallel
>	  self-organizing systems.
>     3.  Engineered artificial life.  (bottom-up approach) ... construction
>	  of robots that function in the real world, using whatever technology
>	  seems appropriate.
>     4.  Study and replication of the detailed structure of biological
>	  intelligence, without necessarily understanding how it works.

Could anyone fill out this tree a little more?

For instance, what about Woods' work on abstract procedures (not to be
confused with proceduralism)?  He wants something more general than logic
-- not throwing it out, but not accepting it as sufficient or appropriate
for the whole job.

What about anything else?  Surely there are "mathematical" theoreticians
that hope for something more than logic, that ought to be included here?
The latest issue of "Computational Intelligence" had more than a score
of responses to Drew McDermott's critique of pure logicism, and one heck
of a lot of camps got staked out in the process.