Minimax Performance in Backgammon

This paper presents the first performance results for Ballard’s *-Minimax algorithms applied to a real–world domain: backgammon. It is shown that with effective move ordering and probing the Star2 algorithm considerably outperforms Expectimax. Star2 allows strong backgammon programs to conduct depth...

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Bibliographische Detailangaben
Hauptverfasser: Hauk, Thomas, Buro, Michael, Schaeffer, Jonathan
Format: Buchkapitel
Sprache:eng
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Beschreibung
Zusammenfassung:This paper presents the first performance results for Ballard’s *-Minimax algorithms applied to a real–world domain: backgammon. It is shown that with effective 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 backgammon does not require deep searches.
ISSN:0302-9743
1611-3349
DOI:10.1007/11674399_4