Weak Ordering Space Search in Turn-based War Chess Gaming

Hai Nan, Wanping Liu, Chao Liu, Chengyun Song
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Abstract

Turn-Based War Chess Game (TBW) is the most important part of turn-based strategy game, and the research on its AI is hard but has a great significant impact not only on video games but also on applied mathematics. This paper is aimed at eliminating order independent redundancy plans in Nan’s enumeration methods. First, we propose the Weak Order Correlation theory, whose necessary and sufficient condition are deduced theoretical. Then, using this theory and its conditions, we design the non-redundant enumeration algorithm in weak order space. Consequently, the completeness and efficiency (zero redundancy of the plans) of the new algorithm are guaranteed.
回合制战棋博弈中的弱排序空间搜索
回合制战争象棋是回合制战略游戏的重要组成部分,其AI研究难度较大,但不仅对电子游戏领域,而且对应用数学领域都有重要影响。本文旨在消除Nan枚举方法中与顺序无关的冗余计划。首先,我们提出了弱序相关理论,并从理论上推导了弱序相关理论的充要条件。然后,利用该理论及其条件,设计了弱序空间下的非冗余枚举算法。从而保证了新算法的完整性和效率(方案零冗余)。
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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