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From: jbarnett@nrtc.northrop.com (Jeff Barnett)
Subject: Looking for search algorithm
Message-ID: <DALFx2.FKn@gremlin.nrtc.northrop.com>
Sender: news@gremlin.nrtc.northrop.com (Usenet News Manager)
Reply-To: jbarnett@charming.nrtc.northrop.com
Organization: Northrop Automation Sciences Laboratory
Date: Thu, 22 Jun 1995 21:34:13 GMT
Lines: 26

[Our news reader has fallen a week or so behind.  Hence, a lot of
 articles are lost.  Therefore, if you respond to this request for
 help, please email a copy to jbarnett@nrtc.northrop.com or I might
 not see it.  Also, if the following is a faq, I haven't been able
 to access it because of our news reader problems.]

The A* algorithm (or variant) seems to be the natural approach to
a problem that I am working on.  I must find a path that maximizes
a measure and that measure is additive, therefore, I can exactly
evaluate partial solutions.  However, producing a good OPTIMISTIC
forward estimator is very difficult.  On the other hand, it is
fairly straightforward to produce a reasonable PESSIMISTIC forward
estimator.

Obviously, I would like to improve this search by using both the
optimistic and pessimistic estimators.  (Note, alpha/beta and its
variants aren't appropriate because the estimators predict path
values, not global values.)  I am looking for ideas or citations
along these lines.

I seem to recall that Hans Berliner did some work in this area.
Perhaps it was the B* algorithm?  Any citations would be good.

Thank you all in advance for any help that you can offer.

Jeff Barnett
