|
JAIST Repository >
School of Transdisciplinary Science >
Articles >
Journal Articles >
Please use this identifier to cite or link to this item:
https://hdl.handle.net/10119/20562
|
| Title: | Proposal and Generation of Endgame Puzzles for an Imperfect Information Game Geister |
| Authors: | Hsueh, Chu-Hsuan
Ishii, Takefumi
Hashimoto, Tsuyoshi
Ikeda, Kokolo |
| Keywords: | Geister
imperfect information
endgame puzzle
content generation
entertainment |
| Issue Date: | 2024-05-31 |
| Publisher: | Elsevier |
| Magazine name: | Entertainment Computing |
| Volume: | 52 |
| Start page: | 100736 |
| DOI: | 10.1016/j.entcom.2024.100736 |
| Abstract: | 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 |
| Material Type: | author |
| Appears in Collections: | d10-1. 雑誌掲載論文 (Journal Articles)
|
Files in This Item:
| File |
Description |
Size | Format |
|---|
| T-IKEDA-K-0930-3.pdf | | 1060Kb | Adobe PDF | View/Open |
|
All items in DSpace are protected by copyright, with all rights reserved.
|
