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http://hdl.handle.net/10119/19676
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| 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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Files in This Item:
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Description |
Size | Format |
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| K-IKEDA-T-0318-9.pdf | | 423Kb | Adobe PDF | View/Open |
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