Mastering Real-Time Control with Delay-Aware Reinforcement Learning


Delay-aware reinforcement learning empowers intelligent systems to perform accurately even when actions or feedback arrive late. By modeling and compensating for real-world delays, it enhances stability, responsiveness, and safety in robotics, autonomous driving, and complex control environments. This approach sets a new standard for achieving reliable real-time decision-making.

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