4 papers
From Pixels to Temporal Correlations: Learning Informative Representations for Reinforcement Learning Pre-training
Jinwen Wang, Youfang Lin, Xiaobo Hu +4
Unsupervised pre-training on large-scale datasets has demonstrated significant potential for improving the sample efficiency and performance of Reinforcement Learning (RL). Given t…
Local Motion Matters: A Deconstruct-Recompose Paradigm for Reinforcement Learning Pre-training from Videos
Jinwen Wang, Youfang Lin, Xiaobo Hu +2
Pre-training on large-scale videos to improve reinforcement learning efficiency is promising yet remains challenging. Existing methods typically treat the agent as an indivisible e…
Task-Relevant Representation Decoupling for Visual Reinforcement Learning Generalization
Jinwen Wang, Youfang Lin, Xiaobo Hu +4
Visual Reinforcement Learning (VRL) has achieved considerable success in solving control tasks. However, generalizing learned policies to new environments remains a major challenge…
Learning Robust Representations via Bidirectional Transition for Visual Reinforcement Learning
Xiaobo Hu, Youfang Lin, Yue Liu +4
Visual reinforcement learning has proven effective in solving control tasks with high-dimensional observations. However, extracting reliable and generalizable representations from…