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Please use this identifier to cite or link to this item: http://hdl.handle.net/10119/19676

Title: Can We Infer Move Sequences in Go from Stone Arrangements?
Authors: Hsueh, Chu-Hsuan
Ikeda, Kokolo
Keywords: Inference
likelihood maximization
simulated annealing
Go
Issue Date: 2024-02-27
Publisher: Springer, Cham
Magazine name: 18th International Conference on Advances in Computer Games (ACG 2023)
Start page: 76
End page: 87
DOI: 10.1007/978-3-031-54968-7_7
Abstract: Inference commonly happens in our daily lives and is also a hot topic for AI research. In this paper, we infer move sequences in Go, i.e., the order in which moves are played, from stone arrangements on the board.We formulate the problem as likelihood maximization and employ a general optimization algorithm, simulated annealing, to solve it. Our experiments on professional and amateur games show that the proposed approach sometimes produces more natural move sequences than those played by humans.
Rights: This is the author's version of the work. Copyright (C) 2024, Chu-Hsuan Hsueh and Kokolo Ikeda, under exclusive license to Springer Nature Switzerland AG. The version published by Springer, Cham is available at https://doi.org/10.1007/978-3-031-54968-7_7
URI: http://hdl.handle.net/10119/19676
Material Type: author
Appears in Collections:d11-1. 会議発表論文 (Conference Papers)

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