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, C