Upper Confidence Bounds for Trees in the Game of Tic-Tac-Toe
Monte-Carlo Tree Search (MCTS) is a best-first tree search algorithm to evaluate states and has been successfully applied to various games, especially to the game of Go. Nowadays, the most of MCTS research uses the Upper Confidence Bounds for Trees (UCT) algorithm, which is a variant of MCTS, to balance exploitation and exploration of states. We evaluate the performance of MCTS and UCT playing against each other in the two-player game of Tic-Tac-Toe. The experimental result shows that the UCT player is slightly better than the MCTS player.
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Document Type: Research Article
Affiliations: 1: Department of Sports Science, Sehan University, South Korea 2: Department of Information and Communication Engineering, Sungkyul University, South Korea
Publication date: November 1, 2016
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