Adapting Rules of Official International Mahjong for Online Players
Chucai Wang, Lingfeng Li, Yunlong Lu, Wenxin Li

TL;DR
This paper analyzes the fairness issues of online international Mahjong using AI self-play data, proposing rule modifications like compensatory points to balance first-mover advantage for online play.
Contribution
It introduces data-driven rule adaptations for online Mahjong, addressing fairness and convenience issues specific to online gameplay environments.
Findings
First-mover advantage identified through AI self-play analysis
Proposed compensatory points improve game fairness online
Online implementation demonstrates practical applicability
Abstract
As one of the worldwide spread traditional game, Official International Mahjong can be played and promoted online through remote devices instead of requiring face-to-face interaction. However, online players have fragmented playtime and unfixed combination of opponents in contrary to offline players who have fixed opponents for multiple rounds of play. Therefore, the rules designed for offline players need to be modified to ensure the fairness of online single-round play. Specifically, We employ a world champion AI to engage in self-play competitions and conduct statistical data analysis. Our study reveals the first-mover advantage and issues in the subgoal scoring settings. Based on our findings, we propose rule adaptations to make the game more suitable for the online environment, such as introducing compensatory points for the first-mover advantage and refining the scores of subgoals…
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Taxonomy
TopicsArtificial Intelligence in Games · Digital Games and Media · Gambling Behavior and Treatments
