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From: AIList-REQUEST@AI.AI.MIT.EDU (AIList Moderator Nick Papadakis)
Newsgroups: comp.ai.digest
Subject: AIList Digest   V7 #7 [babbage!reiter@husc6.harvard.edu: Exciting work in AI]
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Date: 24 May 88 19:32:26 GMT
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Date: 17 May 88 13:19:24 GMT
From: babbage!reiter@husc6.harvard.edu  (Ehud Reiter)
Organization: Aiken Computation Lab Harvard, Cambridge, MA
Subject: Exciting work in AI
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About a month ago, I posted a note asking if any "exciting" work existed
in AI which:
	1) Was highly thought of by at least 50% of AI researchers.
	2) Was a positive contribution, not an analysis showing problems
in previous work.
	3) Was in AI as narrowly defined (i.e. not in robotics or vision)

Well, I'm still looking.  I have received some suggestions, but almost
all of them have seemed problematical.  The most promising were Spencer
Star's suggestions for exciting work in machine learning (published in
a previous AIList, including Valiant's theoretical analyses, Quinlan's
decision trees, and explanation-based learning).  However, after
looking at some books and course syllabi in machine learning, I was
forced to conclude that the topics mentioned by Spencer did not satisfy
condition (1), as the topics he mentioned had very little overlap with
the topics in the books and syllabi (which, incidentally, had very
little overlap with each other).

So, I'm still looking for work which meets the above criteria, and hoping
to thereby convince my friend that there is some cohesion to AI.  If anyone
has suggestions, please send them to me!

					Ehud Reiter
					reiter@harvard	(ARPA,BITNET,UUCP)
					reiter@harvard.harvard.EDU  (new ARPA)