Path: utzoo!utgpu!news-server.csri.toronto.edu!mailrus!cs.utexas.edu!usc!zaphod.mps.ohio-state.edu!uakari.primate.wisc.edu!ames!pacbell!osc!jgk
From: jgk@osc.COM (Joe Keane)
Newsgroups: comp.ai
Subject: Re: NEGMAX question
Summary: NegMax is MiniMax in disguise.
Keywords: search
Message-ID: <2241@osc.COM>
Date: 21 Mar 90 20:35:19 GMT
References: <1778@fredonia.UUCP>
Reply-To: jgk@osc.COM (Joe Keane)
Distribution: usa
Organization: Object Sciences Corp., Menlo Park, CA
Lines: 10

In article <1778@fredonia.UUCP> fredonia!gros1530@cs.buffalo.edu (Dan Gross)
writes:
>	Is the NEGMAX procedure meant to to work with 1,0,-1 evaluation
>ONLY, or can it work with any evaluation with -# for loss and +# for win?
>In other words, will it work if the terminal nodes are something besides the
>basic -1,0,1 (ex. -2.5 -.97 .98 .34 -1.3)?

Yes, it works fine with continuous evaluations.  The difference between it and
MiniMax is minimal; you just flip the signs on every other ply.  It just comes
down to which is easier to code, or runs faster.