Abstract
An Eight Ball pool strategy algorithm with look-ahead is presented. The strategy uses a probabilistically evaluated game search tree to discover the best shot to attempt at each turn. Performance results of the strategy algorithm from a simulated tournament are presented. Players looking further ahead in the search tree performed better against their shallower-searching competitors, at the expense of larger execution time. The advantage of a deeper search tree was magnified for players with greater shooting precision. © Springer-Verlag Berlin Heidelberg 2007.
Cite
CITATION STYLE
Leckie, W., & Greenspan, M. (2007). Monte-Carlo methods in pool strategy game trees. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4630 LNCS, pp. 244–255). Springer Verlag. https://doi.org/10.1007/978-3-540-75538-8_22
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