On the huge benefit of decisive moves in Monte-Carlo Tree Search algorithms
On the huge benefit of decisive moves in Monte-Carlo Tree Search algorithms
复制标题
关于蒙特卡洛树搜索算法中果断行动的巨大好处
DOI：
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发表时间：
2010
期刊：
影响因子：
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通讯作者：
O. Teytaud
中科院分区：
文献类型：
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作者：
F. Teytaud;O. Teytaud
蒙特卡洛树搜索 (MCTS) 算法，包括置信上限 (UCT)，在最困难的棋盘游戏（尤其是围棋游戏）中具有非常好的结果。最近，这些方法已成功引入 Hex 和 Havannah 游戏中。在本文中，我们将定义决定性走法和反决定性走法，并展示它们在 MCTS 中的低计算开销和高效率。
Monte-Carlo Tree Search (MCTS) algorithms, including upper confidence Bounds (UCT), have very good results in the most difficult board games, in particular the game of Go. More recently these methods have been successfully introduce in the games of Hex and Havannah. In this paper we will define decisive and anti-decisive moves and show their low computational overhead and high efficiency in MCTS.