Abstract
In games, Monte-Carlo simulations can be used as an evaluation function for Alpha-Beta search. Assuming w is the width of the search tree, d its depth, and g the number of simulations at each leaf, then the total number of simulations is at least \(g \times (2 \times w^{\frac{d}{2}}\)). In games where moves permute, we propose to replace this algorithm by a new algorithm, Virtual Global Search, that only needs g ×2d simulations for a similar number of games per leaf. The algorithm is also applicable to games where moves often but not always permute, such as Go. We specify the application for 9×9 Go.
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Cazenave, T. (2007). Virtual Global Search: Application to 9×9 Go. In: van den Herik, H.J., Ciancarini, P., Donkers, H.H.L.M.(. (eds) Computers and Games. CG 2006. Lecture Notes in Computer Science, vol 4630. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75538-8_6
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DOI: https://doi.org/10.1007/978-3-540-75538-8_6
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