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arXiv Machine Learning By Nishanth Arun Rao, Royina Karegoudra Jayanth, Benjamin Eysenbach, Jaime Fern\'andez Fisac

A Unified Bellman Operator for Safety-Critical Reinforcement Learning

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The paper introduces a new Bellman operator that merges performance and safety objectives into a single joint value function for reinforcement learning. Temporal difference learning with this operator converges under a two‑timescale stochastic approximation, estimating safety on a fast timescale and joint value on a slow one. Theoretical analysis shows convergence to safety‑constrained optimal policies, and experiments on continuous control tasks confirm stable learning with near‑zero safety violations.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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