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English(EN) SMC-ES: Automated synthesis of formally verified control policies

新算法为自主系统合成形式化验证的控制策略

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了SMC-ES，一种将进化策略与统计模型检查相结合的新算法，可自动合成自主系统的控制策略。该方法对性能、安全性和鲁棒性提供形式化保证，确保遇到违规的概率低于指定阈值。SMC-ES在Gymnasium和Safety Gymnasium的连续控制任务上进行了评估，与领先的深度强化学习和Safe-DRL基线相比，表现具有竞争力，但计算成本有所增加。 AI

影响 增强了自主系统控制策略的形式化验证，可能提高关键应用的信任度和安全性。

排序理由 该集群描述了学术论文中发布的新算法和方法论。

在 arXiv cs.LG 阅读 →

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新算法为自主系统合成形式化验证的控制策略

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报道来源 [2]

  1. arXiv cs.AI TIER_1 English(EN) · Riccardo Curcio, Toni Mancini, Enrico Tronci ·

    SMC-ES：形式化验证控制策略的自动化合成

    arXiv:2607.15003v1 Announce Type: new Abstract: 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 method…

  2. arXiv cs.LG TIER_1 English(EN) · Enrico Tronci ·

    SMC-ES：形式化验证控制策略的自动化合成

    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 fle…

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