Mining experiential patterns from game-logs of board game

Abstract

In board games, game-logs record past game processes, which can be regarded as an accumulation of experience. Similar to a real person, a computer player can gradually increase its skill by learning from game-logs. Therefore, the game becomes more interesting. This paper proposes an extensible approach to mine experiential patterns from increasing game-logs. The computer player improves its strategies by utilizing these growing patterns, just as it acquires experience. To evaluate the effect and performance of the approach, we designed a sample board game as a test platform and elaborated an experiment consisting of a series of tests. Experimental results show that our approach is effective and efficient.