使用单个Conspiracy Number分析游戏进程模式

Zhang Song, H. Iida
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引用次数: 4

摘要

共谋数搜索(Conspiracy Number Search, CNS)是一种最小/最大树搜索算法,试图保证根节点最小/最大值的准确性。由于收敛速度慢,计算共谋数的成本大,其效率较低。然而,阴谋数仍然是衡量“稳定性”的一个有前途的概念,它可以用来分析游戏进程模式。本文提出了一种利用单个共谋数来分析中国象棋棋局进程模式的方法。我们定义了单个共谋数,并将其应用于alpha-beta搜索框架中。在中国象棋最强大的人工智能引擎之一“大象”程序上进行了实验。实验结果表明,单一合谋数可以弥补传统启发式值的不足,并提供更多关于博弈过程的信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using single Conspiracy Number to analyze game progress patterns
Conspiracy Number Search (CNS) is a MIN/MAX tree search algorithm, trying to guarantee the accuracy of the MIN/MAX value of a root node. It suffers from a low efficiency because of its slow convergence and a big cost of computing conspiracy numbers. However, the conspiracy number is still a promising concept for measuring the “stability”, which can be used to analyze game progress patterns. In this paper, we propose a method to analyze game progress patterns in Chinese Chess by using the single conspiracy number. We define the single conspiracy number and apply it in an alpha-beta search framework. Experiments are done on the ElephantEye program which is one of the most powerful AI engines of Chinese Chess. Experimental results show that single conspiracy number can cover the shortage of conventional heuristic values and give more information on the game progress.
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