Haruhiro Yoshimoto

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Monte-Carlo Tree Search (MCTS) is remarkably successful in two-player games, but parallelizing MCTS has been notoriously difficult to scale well, especially in distributed environments. For a distributed parallel search, transposition-table driven scheduling (TDS) is known to be efficient in several domains. We present a massively parallel MCTS algorithm,(More)
Monte Carlo Go is a promising method to improve the performance of computer Go programs. This approach determines the next move to play based on many Monte Carlo samples. This paper examines the relative advantages of additional samples and enhancements for Monte Carlo Go. By par-allelizing Monte Carlo Go, we could increase sample sizes by two orders of(More)
Recently, P2P (peer-to-peer) online game systems have attracted a great deal of public attention. They work without central servers, thus, the maintenance and organization costs have been drastically reduced. However, in P2P systems, it is difficult for game creators to prevent cheats by malicious players, due to the lack of trusted servers. In order to(More)
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