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cs.LG2025
Reevaluating Policy Gradient Methods for Imperfect-Information Games
Max Rudolph, Nathan Lichtle, Sobhan Mohammadpour +6
In the past decade, motivated by the putative failure of naive self-play deep reinforcement learning (DRL) in adversarial imperfect-information games, researchers have developed nu…
cs.LG2019★ 3 cited
Inter-Level Cooperation in Hierarchical Reinforcement Learning
Abdul Rahman Kreidieh, Glen Berseth, Brandon Trabucco +3
Hierarchies of temporally decoupled policies present a promising approach for enabling structured exploration in complex long-term planning problems. To fully achieve this approach…