The Effectiveness of Opponent Modelling in a Small Imperfect Information Game Contents

Opponent modelling is an important issue in games programming today. Programs which do not perform opponent modelling are unlikely to take full advantage of the mistakes made by an opponent. Additionally, programs which do not adapt over time become less of a challenge to players, causing these players to lose interest. While opponent modelling can be a difficult challenge in perfect information games, where the full state of the game is known to all players at all times, it becomes an even more difficult task in games of imperfect information, where players are not always able to observe the actual state of the game. This thesis studies the problem of opponent modelling in Kuhn Poker, a small imperfect information game that contains several properties that make real-world poker games interesting. Two basic types of opponent modelling are studied, explicit modelling and implicit modelling, and their effectiveness is compared.