2 papers
cs.LG2026
Regret-Guided Search Control for Efficient Learning in AlphaZero
Yun-Jui Tsai, Wei-Yu Chen, Yan-Ru Ju +2
Reinforcement learning (RL) agents achieve remarkable performance but remain far less learning-efficient than humans. While RL agents require extensive self-play games to extract u…
cs.LG2025
Decoupled Hierarchical Reinforcement Learning with State Abstraction for Discrete Grids
Qingyu Xiao, Yuanlin Chang, Youtian Du
Effective agent exploration remains a core challenge in reinforcement learning (RL) for complex discrete state-space environments, particularly under partial observability. This pa…