As part of the CPEC Colloquium Series, I am pleased to invite you to the following talk:

André Platzer, Carnegie Mellon University

Title: Safe AI for CPS

on Tuesday, July 2, 2019, 11:15 a.m. at MPI-SWS Saarbruecken, Campus E1 5, room 029

Simultaneous video cast to MPI-SWS Kaiserslautern, Paul Ehrlich Str., Building G26, room 111

Abstract:
Autonomous cyber-physical systems are systems that combine the physics of motion with advanced cyber algorithms to act on their own without close human supervision. The present consensus is that reasonable levels of autonomy, such as for self-driving cars or autonomous drones, can only be reached with the help of artificial intelligence and machine learning algorithms that cope with the uncertainties of the real world. That makes safety assurance even more challenging than it already is in cyber-physical systems (CPSs) with classically programmed control, precisely because AI techniques are lauded for their flexibility in handling unpredictable situations, but are themselves harder to predict.

This talk identifies the logical path toward autonomous cyber-physical systems. With the help of differential dynamic logic (dL) do we provide a logical foundation for developing cyber-physical system models with the mathematical rigor that their safety-critical nature demands. Its ModelPlex technique provides a logically correct way to tame the subtle relationship of CPS models to CPS implementations. The resulting logical monitor conditions can then be exploited to safeguard the decisions of learning agents, guide the optimization of learning processes, and resolve the nondeterminism frequently found in verification models. Overall, logic leads the way in combining the best of both worlds: the strong predictions that formal verification techniques provide alongside the strong flexibility that the use of AI provides.

Bio:
André Platzer is an Associate Professor of Computer Science at Carnegie Mellon University. He develops the logical foundations of cyber-physical systems to characterize their fundamental principles and to answer the question how we can trust a computer to control physical processes. André Platzer has a Ph.D. from the University of Oldenburg, Germany, received an ACM Doctoral Dissertation Honorable Mention and NSF CAREER Award, and was named one of the Brilliant 10 Young Scientists by the Popular Science magazine and one of the AI’s 10 to Watch by the IEEE Intelligent Systems Magazine.

Please contact me (finkbeiner@cs.uni-saarland.de) if you would like to meet with André.