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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:
https://hdl.handle.net/10119/20562
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| タイトル: | Proposal and Generation of Endgame Puzzles for an Imperfect Information Game Geister |
| 著者: | Hsueh, Chu-Hsuan
Ishii, Takefumi
Hashimoto, Tsuyoshi
Ikeda, Kokolo |
| キーワード: | Geister
imperfect information
endgame puzzle
content generation
entertainment |
| 発行日: | 2024-05-31 |
| 出版者: | Elsevier |
| 誌名: | Entertainment Computing |
| 巻: | 52 |
| 開始ページ: | 100736 |
| DOI: | 10.1016/j.entcom.2024.100736 |
| 抄録: | Geister is a two-player imperfect information game played with two kinds of pieces, blue and red, where each player cannot observe the colors of the opponent's pieces on the board. In this paper, we propose Geister endgame puzzles for players to enjoy the game in another form or to practice figuring out moves that are proven to win, similar to chess mating problems. In Geister endgame puzzles, the goal is to find the shortest winning moves under the assumption of the worst cases. We propose not-revealed and partly-revealed puzzles according to how the opponent's piece colors are revealed to the player. We also propose two kinds of special puzzles, capture-win and red-wall, that utilize specific victory conditions of Geister. We generate Geister endgame puzzles by randomly placing pieces on the board and then using a solver to check whether winning moves exist. The generation success rates for not-revealed and partly-revealed puzzles are approximately 20% to 30%. The experiments also show that puzzles with more moves to win are less frequently generated. In addition, we conduct preliminary experiments that invite beginners to evaluate generated puzzles, which shows that longer-win and special puzzles tend to be more difficult and interesting, respectively. |
| Rights: | Copyright (C) 2024 Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International license (CC BY-NC-ND 4.0). [http://creativecommons.org/licenses/by-nc-nd/4.0/] NOTICE: This is the author's version of a work accepted for publication by Elsevier. Chu-Hsuan Hsueh, Takefumi Ishiia, Tsuyoshi Hashimoto, Kokolo Ikeda, Entertainment Computing, Volume 52, 2025, 100736, https://doi.org/10.1016/j.entcom.2024.100736. |
| URI: | https://hdl.handle.net/10119/20562 |
| 資料タイプ: | author |
| 出現コレクション: | d10-1. 雑誌掲載論文 (Journal Articles)
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このアイテムのファイル:
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記述 |
サイズ | 形式 |
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| T-IKEDA-K-0930-3.pdf | | 2498Kb | Adobe PDF | 見る/開く |
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