Note: [1] Institute of Information Science, Academia Sinica, Taipei, Taiwan. email:brain@iis.sinica.edu.tw
Note: [2] Institute of Information Science, Academia Sinica, Taipei, Taiwan. email:changhungjui@gmail.com
Note: [3] Department of Information Management, Chang Jung Christian University, Tainan, Taiwan. email:schsu@mail.cjcu.edu.tw
Note: [4] Department of Applied Mathematics, Chung Yuan Christian University, Taoyuan, Taiwan. email:jcchen@cycu.edu.tw
Note: [5] Corresponding author. Institute of Information Science, Academia Sinica, Taipei, Taiwan. email:tshsu@iis.sinica.edu.tw
Abstract: The proper evaluation of a possible transition from the middle game to the endgame is an important research issue. We constructed an endgame knowledge base that consists of a large set of endgame heuristics that supports the evaluation. Moreover, a general graph model is proposed to resolve conflicts between two competing material combinations. However, it turned out to be difficult to find such competing material combinations. We need better meta-knowledge rules to find more potential conflicts. In this article, we propose five meta-knowledge rules for Chinese chess. Two examples of meta-knowledge rules are piece exchanges and pawn exchanges. The meta-knowledge rules are inducted from real games played by masters. The heuristics so found are endowed with confidence factors to show their chances of being correct. Using this method, 20% of a previous constructed body of endgame knowledge, consisting of 124, 747 material combinations, was found to be erroneous. About 82.13% of these heuristic errors are auto-corrected using our algorithm. By using the corrected knowledge base, the strength of our game-playing program, CONTEMPLATION, is clearly improved according to self-play tests.
DOI: 10.3233/ICG-2014-37103
Journal: ICGA Journal, vol. 37, no. 1, pp. 17-24, 2014
