Amazons Discover Monte-Carlo
Amazons Discover Monte-Carlo
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亚马逊探索蒙特卡洛
DOI：
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发表时间：
2008
期刊：
影响因子：
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通讯作者：
Richard J. Lorentz
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文献类型：
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作者：
Richard J. Lorentz
蒙特卡罗算法和它们的类似UCT的后继者最近在围棋程序中显示出了非凡的前景。我们将其中一些相同的算法应用到亚马逊游戏程序中。我们的实验表明，用于扮演亚马逊人的纯MC/UCT类型的程序前景不大，但通过使用强大的评估函数，我们能够创建一个混合的MC/UCT程序，它优于基本的MC/UCT程序和传统的基于Minimax的程序。MC/UCT程序能够在锦标赛时间控制的80%以上的时间内击败入侵者，这是一个强大的极大极小程序。
Monte-Carlo algorithms and their UCT-like successors have recently shown remarkable promise for Go-playing programs. We apply some of these same algorithms to an Amazons-playing program. Our experiments suggest that a pure MC/UCT type program for playing Amazons has little promise, but by using strong evaluation functions we are able to create a hybrid MC/UCT program that is superior to both the basic MC/UCT program and the conventional minimax-based programs. The MC/UCT program is able to beat Invader , a strong minimax program, over 80% of the time at tournament time controls.