*-Minimax Performance in Backgammon | Zendy

Thomas Hauk | Zendy; Michael Buro | Zendy; Jonathan Schaeffer | Zendy

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*-Minimax Performance in Backgammon

Author(s) -

Thomas Hauk,

Michael Buro,

Jonathan Schaeffer

Publication year - 2006

Publication title -

lecture notes in computer science

Language(s) - English

Resource type - Book series

SCImago Journal Rank - 0.249

H-Index - 400

eISSN - 1611-3349

pISSN - 0302-9743

ISBN - 3-540-32488-7

DOI - 10.1007/11674399_4

Subject(s) - tournament , minimax , computer science , pruning , domain (mathematical analysis) , algorithm , artificial intelligence , mathematical optimization , mathematics , combinatorics , mathematical analysis , agronomy , biology

This paper presents the rst performance results for Bal- lard's *-Minimax algorithms applied to a real{world domain: backgam- mon. It is shown that with eectiv e move ordering and probing the Star2 algorithm considerably outperforms Expectimax. Star2 allows strong backgammon programs to conduct depth 5 full-width searches (up from 3) under tournament conditions on regular hardware without using risky forward pruning techniques. We also present empirical evidence that with today's sophisticated evaluation functions good checker play in backgam- mon does not require deep searches.

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