A probabilistic bound is derived showing that safety after zero-shot RL deployment in cascade systems depends on the tracking quality achieved by a low-level controller for the inner states.
End-to-end safe reinforcement learning through barrier functions for safety-critical continuous control tasks
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Safety Guarantees in Zero-Shot Reinforcement Learning for Cascade Dynamical Systems
A probabilistic bound is derived showing that safety after zero-shot RL deployment in cascade systems depends on the tracking quality achieved by a low-level controller for the inner states.