Trajectory-based data augmentation exploits geometric relationships between rewards, values, and logging policies to enable effective offline RL from few suboptimal trajectories.
Application of deep learning in active alignment leads to high-efficiency and accurate camera lens assembly
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Trajectory-Level Data Augmentation for Offline Reinforcement Learning
Trajectory-based data augmentation exploits geometric relationships between rewards, values, and logging policies to enable effective offline RL from few suboptimal trajectories.