Time management for Monte-Carlo tree search in Go

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Abstract

The dominant approach for programs playing the game of Go is nowadays Monte-Carlo Tree Search (MCTS). While MCTS allows for fine-grained time control, little has been published on time management for MCTS programs under tournament conditions. This paper investigates the effects that various time-management strategies have on the playing strength in Go. We consider strategies taken from the literature as well as newly proposed and improved ones. We investigate both semi-dynamic strategies that decide about time allocation for each search before it is started, and dynamic strategies that influence the duration of each move search while it is already running. In our experiments, two domain-independent enhanced strategies, EARLY-C and CLOSE-N, are tested; each of them provides a significant improvement over the state of the art. © 2012 Springer-Verlag.

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Baier, H., & Winands, M. H. M. (2012). Time management for Monte-Carlo tree search in Go. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7168 LNCS, pp. 39–51). https://doi.org/10.1007/978-3-642-31866-5_4

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