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cs.LG2025
Exploration by Random Distribution Distillation
Zhirui Fang, Kai Yang, Jian Tao +4
Exploration remains a critical challenge in online reinforcement learning, as an agent must effectively explore unknown environments to achieve high returns. Currently, the main ex…
cs.LG2024
CDSA: Conservative Denoising Score-based Algorithm for Offline Reinforcement Learning
Zeyuan Liu, Kai Yang, Xiu Li
Distribution shift is a major obstacle in offline reinforcement learning, which necessitates minimizing the discrepancy between the learned policy and the behavior policy to avoid…
cs.LG2023★ 3 cited
Replay-enhanced Continual Reinforcement Learning
Tiantian Zhang, Kevin Zehua Shen, Zichuan Lin +4
Replaying past experiences has proven to be a highly effective approach for averting catastrophic forgetting in supervised continual learning. However, some crucial factors are sti…