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Evidence record 11602 · automatically gathered

SMC-ES: Automated synthesis of formally verified control policies

The deployment of autonomous cyber-physical systems in safety-critical environments requires closed-loop control strategies (i.e., policies) that are not only performant but also provably safe and robust. While learning-based methodologies such as Reinforcement Learning offer flexible and scalable approaches to automatically synthesize such controllers, they typically lack the formal guarantees necessary for safe deployment. To bridge this gap, we propose a novel simulation-based methodology to

Record details

Published: 16 July 2026
Source: arXiv cs.AI
Category: Research
Topics: Military & security · Environment
Retrieved: 18 July 2026

source-onlyevidence status

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How to cite this record

ethics.ai (16 July 2026), “SMC-ES: Automated synthesis of formally verified control policies,” evidence record 11602, https://ethics.ai/record/11602 (originally published by arXiv cs.AI).

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