Shun-Chin Hsu

Construction of Chinese Chess Endgame Databases by Retrograde Analysis

Retrograde analysis is well-known and has been successfully developed in the design ofWestern chess1 endgame databases. However, there is little achievement using this technique in the construction of Chinese chess endgame databases. Although the two types of chess have the same number of pieces, similar individual characteristics for pieces, and comparable scales of the size of the boards, the fundamental differences in their playing rules lead to different construction schemes and results of endgame databases. In this paper, we describe our approach to the construction of Chinese Chess Endgame Databases when only one of the players possesses attacking piece(s). We show the results we have in constructing and analyzing a set of 151 endgame databases with a total of at most two attacking pieces, four defending pieces and two Kings. Our databases can be used by Chinese chess computer playing systems and computer aided Chinese chess training systems.

Aggregating consistent endgame knowledge in Chinese Chess

We often incorporate endgame heuristics as part of the evaluation function for Chinese Chess programs. In order to aggregate endgame knowledge effectively, we propose a Chinese Chess endgame knowledge-based system to construct a large set of consistent endgame heuristics, called endgame knowledge base, which is used in our program, Contemplation. The knowledge-based system consists of the acquisition module, the inference module, the inquiry module and the verification module. This system implements our graph model that has the functionality of maintaining consistency and improving its correctness. The experimental results on self-play test show that the playing strength of Contemplation has a distinct enhancement with this knowledge base.

Conflict resolution of chinese chess endgame knowledge base

Endgame heuristics are often incorperated as part of the evaluation function used in Chinese Chess programs. In our program, Contemplation, we have proposed an automatic strategy to construct a large set of endgame heuristics. In this paper, we propose a conflict resolution strategy to eliminate the conflicts among the constructed heuristic databases, which is called endgame knowledge base. In our experiment, the correctness of the obtained constructed endgame knowledge base is sufficiently high for practical usage.

Knowledge Inferencing on Chinese Chess Endgames

Several Chinese chess programs exhibit grandmaster playing skills in the opening and middle game. However, in the endgame phase, the programs only apply ordinal search algorithms; hence, they usually cannot exchange pieces correctly. Some researchers use retrograde algorithms to solve endgames with a limited number of attack pieces, but this approach is often not practical in a real tournament. In a grandmaster game, the players typically perform a sequence of material exchanges between the middle game and the endgame, so computer programs can be useful. However, there are about 185 million possible combinations of material in Chinese chess, and many hard endgames are inconclusive even to human masters. To resolve this problem, we propose a novel strategy that applies a knowledge-inferencing algorithm on a sufficiently small database to determine whether endgames with a certain combination of material are advantageous to a player. Our experimental results show that the performance of the algorithm is good and reliable. Therefore, building a large knowledge database of material combinations is recommended.

Pattern Matching in Go Game Records

Many professional Go games, Go life-and-death problems and others are saved as digital game records by SGF (smart game format). Valuable information hides in these records. This article presents a novel Go game record information retrieval system. In this system, the most difficult part is Go pattern matching in Go game records. In this article, a Go pattern matching algorithm is given to find game records that contain a desired query pattern. Then, a proposed index structure for a Go record database integrates methods of information retrieval and domain knowledge of Go. This index can increase the speed of pattern matching in the game database.

Indefinite Sequence of Moves in Chinese Chess Endgames

In western chess, retrograde analysis has been successfully applied to construct 6-piece endgame databases. This classical algorithm first determines all terminal win or loss positions, i.e., those that are either checkmate or stalemate, and then propagates the values back to their predecessors until no further propagation is possible. The un-propagated positions are then declared draws.

Advanced Meta-knowledge for Chinese Chess Endgame Knowledge Bases

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.

Multilevel Inference in Chinese Chess Endgame Knowledge Bases

In Chinese chess, retrograde analysis can be used to solve complex elementary (i.e., fundamental) endgames and to provide perfect play. However, there are still many practical endgames pending to be analysed due to problems related to the complex playing rules. Of course, there is heuristic endgame knowledge for the evaluation functions. This knowledge is often applied to the complex endgames or the real endgames to improve the playing strength. One crucial problem is to choose relatively advantageous endgames by selecting appropriate piece exchanges. For this problem, we designed a Chinese chess endgame knowledge-based system with a large set of endgame heuristics, called an endgame knowledge base. We use this knowledge base in our program, CONTEMPLATION. To maintain the quality of the constructed knowledge base, it is important to detect and resolve conflicts between the heuristics. A conflict-resolution method enables Chinese chess experts to correct erroneous entries by using knowledge about two endgames that differ by precisely one piece. The problem involves detecting potential errors so that a human expert can easily revise and improve the reliability of the knowledge base. In this article, we introduce two major enhancements to the above method. First, we propose a general graph model to handle the heuristics when the endgames involved are differing in more than one piece. Second, we add a confidence-factor parameter to encode the probability that a heuristic may be true. Such heuristics are often used in real games when pieces are exchanged. The resulting graph model is effective in maintaining the consistency of predefined meta-knowledge, and thus improves the overall quality significantly. The results of the experiments on self-play tests demonstrate that the derived knowledge base improves the playing strength of CONTEMPLATION.

Integration of Chinese Chess Endgame Knowledge Bases

We often incorporate endgame heuristics as part of the evaluation function for CHINESE CHESS programs. We propose a semi-automatic strategy to construct a large set of endgame heuristics, which is called endgame knowledge base, which is used in our program, Contemplation. We also handle the conflict problem in large amount of knowledge. By applying the semi-automatic construction and modification process, we can obtain a consistent endgame knowledge base. Finally, we discuss about our method to achieve high correctness for practical usage.

An Intelligent Tutoring System of Chinese Chess

Computer Chinese chess is an application of artificial intelligence. The playing strength of many Chinese chess programs is at the level of human masters or grandmasters. However, it is not easy for a human player to learn Chinese chess skills from these strong programs because their outputs are no more than moves and score values. It is necessary for a student to understand why he or she loses the game and to receive feedback after practice. In this paper, we propose an intelligent tutoring system for learning Chinese chess. The system interacts with students by playing games with them and gives comments and suggestions to them during a game without any human intervention. After some iterations of practice, our system reports their learning achievements by analyzing their game records.