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

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

22 July 2023
Shiheng Wang
    OffRL
ArXiv (abs)PDFHTML

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

1 / 1 papers shown
Title
RL-CFR: Improving Action Abstraction for Imperfect Information
  Extensive-Form Games with Reinforcement Learning
RL-CFR: Improving Action Abstraction for Imperfect Information Extensive-Form Games with Reinforcement Learning
Boning Li
Zhixuan Fang
Longbo Huang
42
0
0
07 Mar 2024
1