• Journal of Korea Game Society
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• v.18 no.6
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• pp.59-68
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• 2018

In spite of its simple rule, Go is one of the most complex strategic board games in the field of Artificial Intelligence (AI). Monte-Carlo Tree Search (MCTS) is an algorithm with best-first tree search, and has used to implement computer Go. We try to find the most promising first move using MCTS for playing a Go game on a board of size smaller than $9{\times}9$ Go board. The experimental result reveals that MCTS prefers to place the first move at the center in case of odd-sized Go boards, and at the central in case of even-sized Go boards.