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Symmetries and Search in Trick-Taking Card Games Open Access


Other title
card games
heuristic search
Type of item
Degree grantor
University of Alberta
Author or creator
Furtak, Timothy M
Supervisor and department
Buro, Michael (Computing Science)
Examining committee member and department
Korf, Richard (Computer Science, University of California, Los Angeles)
Szafron, Duane (Computing Science)
Holte, Robert (Computing Science)
Mueller, Martin (Computing Science)
Department of Computing Science

Date accepted
Graduation date
Doctor of Philosophy
Degree level
In this dissertation we consider the problem of cardplay move evaluation in the context of trick-taking card games, specifically the German card game Skat, and to a lesser extent Contract Bridge. To this end we construct symmetry-based search extensions for efficiently solving perfect information game states, for use in a Monte Carlo-based high-performance computer Skat player. We extend these symmetries to construct precomputed endgame lookup tables, reducing search time substantially. Finally, we show that recursive rollout-based move selection techniques can achieve superior performance in Skat and a broad class of parameterized games, with respect to both tournament performance and game-theoretic exploitability.
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
Citation for previous publication
Timothy Furtak and Michael Buro. Minimum proof graphs and fastest-cut-first search heuristics. In Proceedings of the 21st International Joint Conference on Artificial Intelligence (IJCAI), 2009Timothy Furtak and Michael Buro. Using payoff-similarity to speed up search. In Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI), 2011Timothy Furtak and Michael Buro. Recursive Monte Carlo search for imperfect information games. In IEEE Conference on Computational Intelligence in Games, 2013

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