Interpretable Concept Bottlenecks to Align Reinforcement Learning Agents

Neural Information Processing Systems 

Goal misalignment, reward sparsity and difficult credit assignment are only a few of the many issues that make it difficult for deep reinforcement learning (RL) agents to learn optimal policies.

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