demonstration retrieval 1generative models 1offline reinforcement learning 1policy generalization 1retrieval-based planning 1
From the 1 of 3 linked papers with an AI index.
3 papers
cs.LG2026
Decoupling Policy Extraction for Offline Reinforcement Learning
Xuyao Lin, Yixiang Shan, Jinru Duan +7
Offline RL methods commonly jointly train the actor and critic, where the critic is used to guide the actor toward higher-value actions. This coupled learning process is well motiv…
cs.AI2026
RAD: Retrieval High-quality Demonstrations to Enhance Decision-making
Lu Guo, Yixiang Shan, Zhengbang Zhu +5
The paper proposes RAD, a method that improves offline reinforcement learning by retrieving high-return states from the dataset and generating sub-trajectories toward these targets…
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…