- 期刊
- OpenAccess
Monte-Carlo Simulation for Mahjong
摘要
Mahjong is a four-player, stochastic, imperfect information game. This paper focuses on the Taiwanese variant of Mahjong, whose complexity is higher than that of Go. We design a strong anytime Monte-Carlo-based Taiwanese Mahjong program. First, we adopt the flat Monte Carlo to calculate the win rates of all afterstates/actions such as discarding each tile. Then, we propose a heuristic method, which we incorporate into flat Monte Carlo to obtain the accurate tile to be discarded. As an anytime algorithm, we can stop simulations and return the current best move at any time. In addition, we prune bad actions to increase accuracy and efficiency. Our program, SIMCAT, won the championship in the Mahjong tournaments in Computer Olympiad 2020 and TAAI 2019/2020.
延伸閱讀
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- 王靜平（2008）。Social Relationship Analysis on Virtual and Real Mahjong〔碩士論文，元智大學〕。華藝線上圖書館。https://doi.org/10.6838/YZU.2008.00010
- 郭桐甫（2017）。Design and Implementation of the computer Taiwan Mahjong Program TimeoutKing〔碩士論文，長榮大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0015-1901201711484500
- Chang, H. H. (2018). Monte Carlo Simulation on CoVaR [master's thesis, National Taiwan University]. Airiti Library. https://doi.org/10.6342/NTU201801699
- 林宗翰（2021）。Using the Enhancement Strategy from Discarded-Tiles Information to Improve Mahjong Program〔碩士論文，國立臺灣師範大學〕。華藝線上圖書館。https://doi.org/10.6345/NTNU202101337