Knowledge abstraction in Chinese chess endgame databases

Authors:
Bo-Nian Chen;Pangfeng Liu;Shun-Chin Hsu;Tsan-sheng Hsu
Affiliations:
Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan;Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan;Department of Information Management, Chang Jung Christian University, Tainan, Taiwan;Institute of Information Science, Academia Sinica, Taipei, Taiwan
Venue:
CG'10 Proceedings of the 7th international conference on Computers and games
Year:
2010

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Abstract

Retrograde analysis is a well known approach to construct endgame databases. However, the size of the endgame databases are too large to be loaded into the main memory of a computer during tournaments. In this paper, a novel knowledge abstraction strategy is proposed to compress endgame databases. The goal is to obtain succinct knowledge for practical endgames. A specialized goal-oriented search method is described and applied on the important endgame KRKNMM. The method of combining a search algorithm with a small size of knowledge is used to handle endgame positions up to a limited depth, but with a high degree of correctness.