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Notes on reinforcement learning interpretability

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ORCAID: Oblique Rule-Based Continuous-Action Interpretation for Deep RL Policies
Source note · Jul 8, 2026
The paper introduces ORCAID, a method for extracting interpretable rule-based policies from reinforcement learning (RL) agents in complex environments with continuous action spaces. The method involves training an…

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Notes on reinforcement learning interpretability

ORCAID: Oblique Rule-Based Continuous-Action Interpretation for Deep RL Policies