3 citations · 3 across the 4 of their papers we have counts for
4 papers
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…
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…
World Models with Hints of Large Language Models for Goal Achieving
Zeyuan Liu, Ziyu Huan, Xiyao Wang +5
Reinforcement learning struggles in the face of long-horizon tasks and sparse goals due to the difficulty in manual reward specification. While existing methods address this by add…
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…