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cs.LG2025
Variational OOD State Correction for Offline Reinforcement Learning
Ke Jiang, Wen Jiang, Xiaoyang Tan
The performance of Offline reinforcement learning is significantly impacted by the issue of state distributional shift, and out-of-distribution (OOD) state correction is a popular…
cs.LG2025
Beyond Non-Expert Demonstrations: Outcome-Driven Action Constraint for Offline Reinforcement Learning
Ke Jiang, Wen Jiang, Yao Li +1
We address the challenge of offline reinforcement learning using realistic data, specifically non-expert data collected through sub-optimal behavior policies. Under such circumstan…