Artificial intelligence, and the ability to learn optimized solutions that comply with a set of safety rules, could facilitate the human-based design process of safety-critical systems. However, the reconciliation of state-of-the-art artificial intelligence technology with current safety standards and safety engineering processes is a challenge to be addressed. In this article, this publication describes a method based on optimization and on formal verification for the design of safety-critical systems that are defined by Boolean algebra. Several diverse optimization techniques and a hybrid of these approaches are used to find an optimized design that considers performance requirements, availability rules, and complies with all defined safety rules. Subsequently, this solution is translated into an alternative knowledge representation that can be formally verified and developed in compliance with currently considered safety standards. This method is evaluated with a simplified safety-critical case study.

中文翻译：

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基于布尔代数的安全关键系统软件设计的优化技术和形式验证


人工智能以及学习符合一组安全规则的优化解决方案的能力，可以促进安全关键系统的人性化设计过程。然而，最先进的人工智能技术与当前安全标准和安全工程流程的协调是一个需要解决的挑战。在本文中，本出版物描述了一种基于优化和形式验证的方法，用于设计由布尔代数定义的安全关键系统。多种不同的优化技术和这些方法的混合用于找到考虑性能要求、可用性规则并符合所有定义的安全规则的优化设计。随后，该解决方案被转化为替代知识表示，可以根据当前考虑的安全标准进行正式验证和开发。该方法通过简化的安全关键案例研究进行评估。