Abstract
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.
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© 2006 Springer-Verlag Berlin Heidelberg
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Hauk, T., Buro, M., Schaeffer, J. (2006). *-Minimax Performance in Backgammon. In: van den Herik, H.J., Björnsson, Y., Netanyahu, N.S. (eds) Computers and Games. CG 2004. Lecture Notes in Computer Science, vol 3846. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11674399_4
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DOI: https://doi.org/10.1007/11674399_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-32488-1
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