CIP combines DirectLiNGAM-style causal masks for state-reward and action-reward links with counterfactual data augmentation and an empowerment objective to improve RL sample efficiency.
Object- aware regularization for addressing causal confusion in imitation learning
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Causal Information Prioritization for Efficient Reinforcement Learning
CIP combines DirectLiNGAM-style causal masks for state-reward and action-reward links with counterfactual data augmentation and an empowerment objective to improve RL sample efficiency.