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cs.LG2025
Target-Aligned Fusion for Decision-Sequence Learning under Dynamics Shift
Guojian Wang, Quinson Hon, Xuyang Chen +1
External trajectories can improve offline decision-sequence learning, but dynamics shift may make some source subsequences inconsistent with the target environment. We study how to…
cs.LG2025
Taming OOD Actions for Offline Reinforcement Learning: An Advantage-Based Approach
Xuyang Chen, Keyu Yan, Wenhan Cao +1
Offline reinforcement learning (RL) learns policies from fixed datasets without online interactions, but suffers from distribution shift, causing inaccurate evaluation and overesti…
cs.LG2025
VIPO: Value Function Inconsistency Penalized Offline Reinforcement Learning
Xuyang Chen, Keyu Yan, Guojian Wang +1
Offline reinforcement learning (RL) learns effective policies from pre-collected datasets, offering a practical solution for applications where online interactions are risky or cos…