Automated Decision Making for Safety Critical Applications

Mykel J Kochenderfer, Associate Professor of Aeronautics and Astronautics at Stanford University; Director of the Stanford Intelligent Systems Laboratory (SISL)

– 16 January 2023

Talk summary: Building robust decision-making systems for autonomous systems is challenging. Decisions must be made based on imperfect information about the environment and with uncertainty about how the environment will evolve. In addition, these systems must carefully balance safety with other considerations, such as operational efficiency. Typically, the space of edge cases is vast, placing a large burden on human designers to anticipate problem scenarios and develop ways to resolve them. Mykel J Kochenderfer‘s talk discussed major challenges associated with ensuring computational tractability and establishing trust that their systems will behave correctly when deployed in the real world. He outlined some methodologies for addressing these challenges and pointed to some research applications that can serve as inspiration for building safer systems. 

Speaker bio:  Mykel J Kochenderfer is an Associate Professor of Aeronautics and Astronautics at Stanford University. He is the Director of the Stanford Intelligent Systems Laboratory (SISL), conducting research on advanced algorithms and analytical methods for the design of robust decision making systems. Of particular interest are systems for air traffic control, unmanned aircraft, and automated driving where decisions must be made in uncertain, dynamic environments while maintaining safety and efficiency. Research at SISL focuses on efficient computational methods for deriving optimal decision strategies from high-dimensional, probabilistic problem representations. 

Prior to joining the faculty in 2013, Kochenderfer was at MIT Lincoln Laboratory where he worked on aircraft collision avoidance, leading to the creation of the ACAS X international standard for manned and unmanned aircraft. He received his PhD from the University of Edinburgh in 2006. He received BS and MS degrees in computer science from Stanford University in 2003. Kochenderfer is a Co-director of the Center for AI Safety. He is an Associate Editor of the Journal of Artificial Intelligence Research and the Journal of Aerospace Information Systems. He is an author of the textbooks Decision Making under Uncertainty: Theory and Application (MIT Press, 2015), Algorithms for Optimization (MIT Press, 2019), and Algorithms for Decision Making (MIT Press, 2022).

[Talk organised in collaboration with the Department of Computer Science and Automation]

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