Formal Methods for Safe Autonomous Systems

3-0-9 units · Graduate

Covers formal methods for designing and analyzing autonomous systems. Focuses on both classical and state-of-the-art rigorous methods for specifying, modeling, verifying, and synthesizing various behaviors for systems where embedded computing units monitor and control physical processes. Additionally, covers advanced material on combining formal methods with control theory and machine learning theory for modern safety critical autonomous systems powered by AI techniques such as robots, self-driving cars, and drones. Strong emphasis on the use of various mathematical and software tools to provide safety, soundness, and completeness guarantees for system models with different levels of fidelity.