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Article type: Research Article
Authors: Song, Zhang; * | Iida, Hiroyuki
Affiliations: Japan Advanced Institute of Science and Technology, Ishikawa, Japan
Correspondence: [*] Corresponding author. E-mail: [email protected].
Abstract: Single Conspiracy Number (SCN) is a variant concept of conspiracy number and proof number which indicates the difficulty of a root node changing its MIN/MAX value to a certain score. It makes up the drawbacks of conspiracy number on computing complexity, and can be easily applied into different search frameworks. This paper explores the potential usage of SCN as a long-term position evaluation to understand in-depth game progress patterns. Chinese Chess is chosen as a testbed for this study, whereas a strong AI engine ‘Xiangqi Wizard’ is used. It is implemented with alpha-beta search and modified to produce SCNs during the search process. Experiments are conducted on different types of positions including tactical positions, drawn positions and opening positions. The experimental results show that SCN is more consistent and accurate for long-term position evaluation than the conventional way using evaluation function values only, and using SCN together with evaluation function values enables us to better understand game progress patterns.
Keywords: Single Conspiracy Number, MIN/MAX value, game progress pattern, Chinese Chess
DOI: 10.3233/ICG-180059
Journal: ICGA Journal, vol. 40, no. 3, pp. 269-280, 2018
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