论文标题
AI中的正确构建运行时执行 - 调查
Correct-by-Construction Runtime Enforcement in AI -- A Survey
论文作者
论文摘要
运行时执行是指针对运行时正式规范执行正确行为的理论，技术和工具。在本文中，我们对用于构建AI中实施安全性的混凝土应用程序域的运行时执行器的技术感兴趣。我们讨论了在AI领域传统上如何处理安全性，以及如何通过集成运行时执行器来提供自我学习代理的安全性。我们调查了此类执法者的一系列工作，在该工作中，我们区分了离散和连续动作空间的方法。本文的目的是更好地理解不同执法技术的优势和局限性，重点关注由于AI在AI中的应用而引起的特定挑战。最后，我们为将来的工作提出了一些开放的挑战和途径。
Runtime enforcement refers to the theories, techniques, and tools for enforcing correct behavior with respect to a formal specification of systems at runtime. In this paper, we are interested in techniques for constructing runtime enforcers for the concrete application domain of enforcing safety in AI. We discuss how safety is traditionally handled in the field of AI and how more formal guarantees on the safety of a self-learning agent can be given by integrating a runtime enforcer. We survey a selection of work on such enforcers, where we distinguish between approaches for discrete and continuous action spaces. The purpose of this paper is to foster a better understanding of advantages and limitations of different enforcement techniques, focusing on the specific challenges that arise due to their application in AI. Finally, we present some open challenges and avenues for future work.
