Author: Jay Scott
Date: 12:00:04 11/10/97
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On November 10, 1997 at 06:43:42, Mark Taylor wrote: >Has anyone tried position evaluation by neural network? This is a frequently asked question. It'd be nice if somebody would put together a subject FAQ for computer chess. As a couple replies mention, the obvious ways of using a neural net as an evaluator are not likely to work well, at least not without hardware assist. But the neural net field is huge and diverse. Besides all the great ideas that haven't been had yet, there are a few already known that might be good enough. See the paper "Efficient neural net alpha-beta-evaluators" by Alois Heinz for one idea. These networks accept alpha and beta from the search, and can do alpha-beta cutoffs in the middle of network evaluation. This is a generalization of the lazy evaluation trick that many chess programs use: if the material score is so big that the positional score can't bring it within the alpha- beta window, then evaluation can be cut off. The paper is available online. Here are two web sites which link to it. Alois Heinz's page is in German, but the papers listed at the bottom are in English. http://www.informatik.uni-freiburg.de/~heinz/ My web site, Machine Learning in Games, includes information about learning game programs and methods that can be used in learning programs. chess programs. Follow the "online papers" link for Alois Heinz's paper with my capsule review. http://forum.swarthmore.edu/~jay/learn-game/index.html Jay
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