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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/10119/18467
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| タイトル: | Procedural Maze Generation with Considering Difficulty from Human Players' Perspectives |
| 著者: | Fujihira, Keita
Hsueh, Chu-Hsuan
Ikeda, Kokolo |
| キーワード: | Procedural content generation
RPG
Maze
Difficulty |
| 発行日: | 2022-08-01 |
| 出版者: | Springer, Cham |
| 誌名: | Lecture Notes in Computer Science |
| 巻: | 13262 |
| 開始ページ: | 165 |
| 終了ページ: | 175 |
| DOI: | 10.1007/978-3-031-11488-5_15 |
| 抄録: | In video game development, creating maps, enemies, and many other elements of game levels is one of the important process. In order to improve players' game experiences, game designers need to understand players' behavioral tendencies and create levels accordingly. Among various components of levels, this paper targets mazes and presents an automatic maze generation method with considering difficulty based on human players' tendencies. We first investigate the
tendencies using supervised learning and create a test player considering human-likeness by using the tendencies. The test player simulates human players' behaviors when playing mazes and judges difficulty according to the simulation results. Maze evaluation results of subject experiments show that our method succeeds in generating mazes where the difficulty estimated by the test player matches human players'. |
| Rights: | Copyright Springer Nature Switzerland AG 2022. Keita Fujihira, Chu-Hsuan Hsueh, and Kokolo Ikeda, Lecture Notes in Computer Science, vol 13262. Springer, Cham., 2022. The final publication is available at Springer via https://doi.org/10.1007/978-3-031-11488-5_15 |
| URI: | http://hdl.handle.net/10119/18467 |
| 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:
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記述 |
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| I-IKEDA-K0405-14.pdf | | 659Kb | Adobe PDF | 見る/開く |
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