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Pruning algorithms for multi-model adversary search

delete1998-03-01
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OA
AI
D
David Carmel
S
Shaul Markovitch *
DOI:10.1016/S0004-3702(97)00074-Xdelete
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Abstract

Abstract

En 中文
The multi-model search framework generalizes minimax to allow exploitation of recursive opponent models. In this work we consider adding pruning to the multi-model search. We prove a sufficient condition that enables pruning and describe two pruning algorithms, alpha beta* and alpha beta(1p)* We prove correctness and optimality of the algorithms and provide an experimental study of their pruning power. We show that for opponent models that are not radically different from the player's strategy, the pruning power of these algorithms is significant. (C) 1998 Elsevier Science B.V.
Keywords:
opponent modeling
adversary search
pruning
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Journal

Artificial Intelligence Review cover
Artificial Intelligence Review
IF:
13.9
Papers:
6.1K
Citations:
1.9W

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