Abstract:Monte-Carlo simulations can be used as an evaluation function for Alpha-Beta in games. If w is the width of the search tree, d its depth, and g the number of simulations at each leaf, the total number of simulations is at least g × (2 × w d 2). In games where moves permute, we propose to replace this algorithm by another algorithm that only needs g × 2 d simulations for a similar number of games per leaf. The algorithm can also be applied to games where moves often but not always permute, such as Go. We detail… Show more
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