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Formal Methods for Autonomous Systems 自治系统的形式化方法
Q1 AUTOMATION & CONTROL SYSTEMS Pub Date : 2023-01-01 DOI: 10.1561/2600000029
Tichakorn Wongpiromsarn, Mahsa Ghasemi, Murat Cubuktepe, Georgios Bakirtzis, Steven Carr, Mustafa O. Karabag, Cyrus Neary, Parham Gohari, Ufuk Topcu
Formal methods refer to rigorous, mathematical approaches to system development and have played a key role in establishing the correctness of safety-critical systems. The main building blocks of formal methods are models and specifications, which are analogous to behaviors and requirements in system design and give us the means to verify and synthesize system behaviors with formal guarantees. This monograph provides a survey of the current state of the art on applications of formal methods in the autonomous systems domain. We consider correct-by-construction synthesis under various formulations, including closed systems, reactive, and probabilistic settings. Beyond synthesizing systems in known environments, we address the concept of uncertainty and bound the behavior of systems that employ learning using formal methods. Further, we examine the synthesis of systems with monitoring, a mitigation technique for ensuring that once a system deviates from expected behavior, it knows a way of returning to normalcy. We also show how to overcome some limitations of formal methods themselves with learning. We conclude with future directions for formal methods in reinforcement learning, uncertainty, privacy, explainability of formal methods, and regulation and certification.
形式化方法是指系统开发的严格的数学方法,在建立安全关键系统的正确性方面发挥了关键作用。形式化方法的主要构建模块是模型和规范,它们类似于系统设计中的行为和需求,为我们提供了通过形式化保证来验证和综合系统行为的手段。本专著提供了在自治系统领域的形式方法的应用艺术的现状的调查。我们考虑不同配方下的结构正确合成,包括封闭系统,反应性和概率设置。除了在已知环境中合成系统之外,我们还解决了不确定性的概念,并使用形式化方法约束了采用学习的系统的行为。此外,我们还研究了系统与监控的综合,这是一种缓解技术,用于确保一旦系统偏离预期行为,它就知道恢复正常的方法。我们还展示了如何通过学习来克服形式方法本身的一些局限性。我们总结了强化学习、不确定性、隐私、形式化方法的可解释性以及监管和认证方面形式化方法的未来方向。
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Foundations and Trends in Systems and Control
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