3 citations · 5 across the 7 of their papers we have counts for
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cs.LG2025
ASTRO: Adaptive Stitching via Dynamics-Guided Trajectory Rollouts
Hang Yu, Di Zhang, Qiwei Du +5
Offline reinforcement learning (RL) enables agents to learn optimal policies from pre-collected datasets. However, datasets containing suboptimal and fragmented trajectories presen…
cs.LG2023★ 3 cited
How to Fine-tune the Model: Unified Model Shift and Model Bias Policy Optimization
Hai Zhang, Hang Yu, Junqiao Zhao +5
Designing and deriving effective model-based reinforcement learning (MBRL) algorithms with a performance improvement guarantee is challenging, mainly attributed to the high couplin…
cs.LG2023★ 1 cited
Safe Reinforcement Learning with Dead-Ends Avoidance and Recovery
Xiao Zhang, Hai Zhang, Hongtu Zhou +4
Safety is one of the main challenges in applying reinforcement learning to realistic environmental tasks. To ensure safety during and after training process, existing methods tend…