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Search in games with incomplete information: a case study using Bridge card play
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The solution for the branching factor of the alpha-beta pruning algorithm and its optimality
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Search and Planning under Incomplete Information: A Study Using Bridge Card Play
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Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
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IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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This paper investigates the problems arising in the construction of a program to play the game of contract bridge. These problems include both the difficulty of solving the game's perfect information variant, and techniques needed to address the fact that bridge is not, in fact, a perfect information game. GIB, the program being described, involves five separate technical advances: partition search, the practical application of Monte Carlo techniques to realistic problems, a focus on achievable sets to solve problems inherent in the Monte Carlo approach, an extension of alpha-beta pruning from total orders to arbitrary distributive lattices, and the use of squeaky wheel optimization to find approximately optimal solutions to cardplay problems. GIB is currently believed to be of approximately expert caliber, and is currently the strongest computer bridge program in the world.