A model of two-player evaluation punctions

Authors:
Bruce Abramson;Richard E. Korf
Affiliations:
Department of Computer Science, Columbia University, and Computer Science Department, University of California at Los Angeles;Computer Science Department, University of California at Los Angeles
Venue:
AAAI'87 Proceedings of the sixth National conference on Artificial intelligence - Volume 1
Year:
1987

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Abstract

We present a model of heuristic evaluation functions for two-player games. The basis of the proposal is that an estimate of the expected-outcome of a game situation, assuming random play from that point on, is an effective heuristic function. The model is supported by three distinct sets of experiments. The first set, run on small, exhaustively searched gametrees, shows that the quality of decisions made on the basis of exact values for the expected-outcome is quite good. The second set shows that in large games, estimates of the expected-outcome derived by randomly sampling terminal positions produce reasonable play. Finally, the third set shows that the model can be used to automatically learn efficient and effective evaluation functions in a game-independent manner.