标题： CFR-p：具有分层策略抽象的反事实遗憾最小化及其在二人麻将中的应用 显示英文标题

标题： CFR-p: Counterfactual Regret Minimization with Hierarchical Policy Abstraction, and its Application to Two-player Mahjong

摘要： 反事实遗憾最小化(CFR)在德州扑克中已显示出其成功。 我们将此算法应用于另一种流行的不完全信息游戏——麻将。 与扑克游戏相比，麻将更加复杂，有许多变种。 我们通过进行博弈论分析，并基于获胜策略对CFR进行分层抽象来研究两人麻将。 此框架可以推广到其他不完美信息游戏。 显示英文摘要

摘要： Counterfactual Regret Minimization(CFR) has shown its success in Texas Hold'em poker. We apply this algorithm to another popular incomplete information game, Mahjong. Compared to the poker game, Mahjong is much more complex with many variants. We study two-player Mahjong by conducting game theoretical analysis and making a hierarchical abstraction to CFR based on winning policies. This framework can be generalized to other imperfect information games.