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📄 ResearchJuly 27, 2026

Explainable Reinforcement Learning via Physics-Aware Policy Distillation

In safety-critical sectors such as robotics and automotive engineering, the deployment of Deep Reinforcement Learning (DRL) is often hindered by the black-box nature of deep neural networks. This lack of transparency poses significant challenges for regulatory compliance and human-agent trust. This ...

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Source

http://arxiv.org/abs/2607.24672v1