DEPLOY-RL certifies RL deployment in safety-critical processes by boundary discovery and conservative certification
Read the original at arxiv.org→arXiv:2611.00342v1 Announce Type: new Abstract: Reinforcement learning (RL) policies often outperform classical controllers in simulation, yet rarely reach production in safety-critical processes. The barrier is...
Original headline: "DEPLOY-RL: Active Boundary Discovery and Conservative Certification for Deployable Reinforcement Learning in Safety-Critical Continuous Processes"
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- Nov 3, 05:00 UTC arXiv cs.LG lead source DEPLOY-RL: Active Boundary Discovery and Conservative Certification for Deployable Reinforcement Learning in Safety-Critical Continuous Processes