报告名称：Trustworthy-by-Design Autonomous AI Systems

报告时间：2月18日 13：30

报告地点：理科大楼B1002

报告摘要:

There has been a fast-growing trend in developing autonomous artificial intelligence (AI) systems operating in dynamic, partially known, and unpredictable environments. Autonomous AI systems must self-deliberate to accomplish tasks, especially in challenging situations when human instructions are lacking or delayed, e.g., NASA's Mars 2020 Perseverance rover. Yet, these systems must be trustworthy, as empowering AI systems with the ability to self-deliberate carries significant risks. This necessitates a crucial need for guarantees that suitable trustworthiness in the action and decision making of the AI systems is always respected, especially for safety-critical and security-critical applications. Reactive synthesis, originated from formal methods (FM), emerges as a trustworthy-by-design technique in developing verifiably correct controllers for autonomous AI systems. This talk puts a particular focus on reactive synthesis of Linear Temporal Logic on finite traces (LTLf), which has established its scalability and applicability in utilizing reactive synthesis for building trustworthy autonomous AI systems. We will present in this talk an overview of key advancements in LTLf synthesis, highlighting its scalability and potential in complex scenarios. These results base on a so-called DFA-technology, which essentially takes the maximal simplicity of reasoning about efficiently constructed deterministic finite word automaton (DFA) of the LTLf objective. The talk will conclude with a discussion of promising research directions aimed at developing computationally scalable techniques for trustworthy autonomous AI systems in real-world applications.

报告人简介:

Shufang Zhu is a Lecturer (Assistant Professor in US terms) at the Department of Computer Science, University of Liverpool. She is also an Associate Member of the Department of Computer Science, University of Oxford. Prior to joining Liverpool, she was a Senior Research Associate at the Department of Computer Science, University of Oxford. Her expertise lies in the interdisciplinary research area of artificial intelligence (AI) and formal methods (FM), with a focus on automated planning and synthesis.