Macroscopic understanding of the game situations in GO

T. Yokogawa, J. Nishino, Y. Mizuno
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引用次数: 1

Abstract

Chess program has a great progress by a method of game tree search. In the contrary, the search method does not work well in GO, because GO has much vaster search space. In this paper, we propose that a fuzzy approach can be applied to GO algorithm; especially for understanding of "Atsumi(thickness)". "Atsumi" is treated as mixed fuzzy values of various axes similar to ones human players use when they decide the strategy. We also propose that general rules of GO strategy can be written by "Atsumi" and show that the approach is applicable to open game or beginning of middle game of GO.<>
对围棋游戏情境的宏观理解
国际象棋程序有很大的进步,通过游戏树搜索的方法。相反,这种搜索方法在GO中并不好用,因为GO的搜索空间要大得多。在本文中,我们提出了一种模糊方法可以应用于GO算法;特别是对于“厚度”的理解。“Atsumi”被视为各种轴的混合模糊值,类似于人类玩家在决定策略时使用的轴。我们还提出了围棋策略的一般规则可以由“Atsumi”编写,并表明该方法适用于围棋的开放局或中间局开始。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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