Incorporating Opponent Models into Adversary Search

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Incorporating Opponent Models into Adversary Search
This work presents a generalized theoretical framework that allows incorporation of opponent models into adversary search. We present the M algorithm, a generalization of minimax that uses an arbitrary opponent model to simulate the opponent's search. The opponent model is a recursive structure consisting of the opponent's evaluation function and its model of the player. We demonstrate experimentally the potential benefit of using an opponent model. Pruning in M is impossible in the general case. We prove a sufficient condition for pruning and present the algorithm which returns the M value of a tree while searching only necessary branches.
David Carmel, Shaul Markovitch
Added 02 Nov 2010
Updated 02 Nov 2010
Type Conference
Year 1996
Where AAAI
Authors David Carmel, Shaul Markovitch
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