Strategy Acquisition for the Game "Othello" Based on Reinforcement Learning
نویسندگان
چکیده
This article discusses automatic strategy acquisition for the game \Othello" based on reinforcement learning. In our approach, two computer players initially know only the game rules, but they become relatively stronger after playing several thousands of games against each other. In each game, the players re ne the evaluation function for the game state, which is achieved in a reinforcement learning manner. Since the state space is very large, we employ an RBF (Radial Basis Functions) network to approximate the evaluation function. As a result, the players become strong enough to beat a player employing a heuristic strategy.
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