CHANCEPROBCUT: Forward pruning in chance nodes

Maarten P D Schadd, Mark H M Winands, Jos W H M Uiterwijk

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review

Abstract

This article describes a new, game-independent forward-pruning technique for EXPECTIMAX, called CHANCEPROBCUT. It is the first technique to forward prune in chance nodes. Based on the strong correlation between evaluations obtained from searches at different depths, the technique prunes chance events if the result of the chance node is likely to fall outside the search window. In this article, CHANCEPROBCUT is tested in two games, i.e., Stratego and Dice. Experiments reveal that the technique is able to reduce the search tree significantly without a loss of move quality. Moreover, in both games there is also an increase of playing performance. ©2009 IEEE.
Original languageEnglish
Title of host publicationCIG2009 - 2009 IEEE Symposium on Computational Intelligence and Games
Pages178-185
Number of pages8
DOIs
Publication statusPublished - 2009

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