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Found 3 papers, 1 papers with code
Causal Action Influence Aware Counterfactual Data Augmentation
Offline data are both valuable and practical resources for teaching robots complex behaviors.
Efficient Learning of High Level Plans from Play
Real-world robotic manipulation tasks remain an elusive challenge, since they involve both fine-grained environment interaction, as well as the ability to plan for long-horizon goals.
Risk-Averse Offline Reinforcement Learning
We demonstrate empirically that in the presence of natural distribution-shifts, O-RAAC learns policies with good average performance.
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