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このアイテムの引用には次の識別子を使用してください:
http://hdl.handle.net/10119/19676
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タイトル: | Can We Infer Move Sequences in Go from Stone Arrangements? |
著者: | Hsueh, Chu-Hsuan Ikeda, Kokolo |
キーワード: | Inference likelihood maximization simulated annealing Go |
発行日: | 2024-02-27 |
出版者: | Springer, Cham |
誌名: | 18th International Conference on Advances in Computer Games (ACG 2023) |
開始ページ: | 76 |
終了ページ: | 87 |
DOI: | 10.1007/978-3-031-54968-7_7 |
抄録: | 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 |
資料タイプ: | author |
出現コレクション: | d11-1. 会議発表論文 (Conference Papers)
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このアイテムのファイル:
ファイル |
記述 |
サイズ | 形式 |
K-IKEDA-T-0318-9.pdf | | 423Kb | Adobe PDF | 見る/開く |
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