2 papers
cs.AI2025
RAD: Retrieval High-quality Demonstrations to Enhance Decision-making
Lu Guo, Yixiang Shan, Zhengbang Zhu +5
Offline reinforcement learning (RL) learns policies from fixed datasets, thereby avoiding costly or unsafe environment interactions. However, its reliance on finite static datasets…
cs.LG2024
Contrastive Diffuser: Planning Towards High Return States via Contrastive Learning
Yixiang Shan, Zhengbang Zhu, Ting Long +4
The performance of offline reinforcement learning (RL) is sensitive to the proportion of high-return trajectories in the offline dataset. However, in many simulation environments a…