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An Intelligent Othello Player Combining Machine Learning And Game Specific Heuristics, Kevin Anthony Cherry

LSU Master's Theses

Artificial intelligence applications in board games have been around as early as the 1950's, and computer programs have been developed for games including Checkers, Chess, and Go with varying results. Although general game-tree search algorithms have been designed to work on games meeting certain requirements (e.g. zero-sum, two-player, perfect or imperfect information, etc.), the best results, however, come from combining these with specific knowledge of game strategies. In this MS thesis, we present an intelligent Othello game player that combines game-specific heuristics with machine learning techniques in move selection. Five game specific heuristics, namely corner detection, killer move detection, blocking, …