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The UCT algorithm applied to find the best first move in the game of Tic-Tac-Toe
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  • Journal title : Journal of Korea Game Society
  • Volume 15, Issue 5,  2015, pp.109-118
  • Publisher : Korea Game Society
  • DOI : 10.7583/JKGS.2015.15.5.109
 Title & Authors
The UCT algorithm applied to find the best first move in the game of Tic-Tac-Toe
Lee, Byung-Doo; Park, Dong-Soo; Choi, Young-Wook;
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The game of Go originated from ancient China is regarded as one of the most difficult challenges in the filed of AI. Over the past few years, the top computer Go programs based on MCTS have surprisingly beaten professional players with handicap. MCTS is an approach that simulates a random sequence of legal moves until the game is ended, and replaced the traditional knowledge-based approach. We applied the UCT algorithm which is a MCTS variant to the game of Tic-Tac-Toe for finding the best first move, and compared it with the result generated by a pure MCTS. Furthermore, we introduced and compared the performances of epsilon-Greedy algorithm and UCB algorithm for solving the Multi-Armed Bandit problem to understand the UCB.
Go;Tic-Tac-Toe;MCTS;UCT;Multi-Armed Bandit;epsilon-Greedy;UCB;
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