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ACG
2003
Springer

Opponent-Model Search in Bao: Conditions for a Successful Application

10 years 6 months ago
Opponent-Model Search in Bao: Conditions for a Successful Application
Abstract Opponent-Model search is a game-tree search method that explicitly uses knowledge of the opponent. There is some risk involved in using Opponent-Model search. Both the prediction of the opponent’s moves and the estimation of the profitability of future positions should be of good quality and as such they should obey certain conditions. To investigate the role of prediction and estimation in actual computer game-playing, experiments with Opponent-Model search were performed in the game of Bao. After five evaluation functions had been generated using machine-learning techniques, a series of tournaments between these evaluation functions was executed. They showed that Opponent-Model search can be applied successfully, provided that the conditions are met.
H. H. L. M. Donkers, H. Jaap van den Herik, Jos W.
Added 06 Jul 2010
Updated 06 Jul 2010
Type Conference
Year 2003
Where ACG
Authors H. H. L. M. Donkers, H. Jaap van den Herik, Jos W. H. M. Uiterwijk
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