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Learning When to Act: Communication-Efficient Reinforcement Learning via Run-Time Assurance

arXiv cs.LG ↗ · 2026-05-14 Cached

This paper presents a framework (CARE) that jointly learns control inputs and communication-efficient timing decisions under a pointwise Lyapunov safety shield, achieving higher inter-sample intervals than classical methods on inverted pendulum, cart-pole, and planar quadrotor systems.

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