Stanford AA289/ENGR319 - Robotics and Autonomous Systems Seminar - Stanford Seminar - On human-machine interaction games

April 11, 2025 Sam Burden, UW Seattle Our work is broadly motivated by the emergence of learning-based methods in control theory and robotics, with a specific focus on scenarios that have humans in-the-loop with control systems. For instance, learning algorithms are being deployed in semi-autonomous vehicles, robot assistants, brain-machine interfaces, and exoskeletons, where they interact dynamically with a human partner to complete tasks. When learning algorithms are employed in this way, a dynamic game is created that is played between two intelligent agents (the human and machine learners), requiring new techniques to guarantee safety and performance. About the speaker: https://faculty.washington.edu/sburden/bio/ More about the course can be found here: https://stanfordasl.github.io/robotics_seminar/ View the entire AA289 Stanford Robotics and Autonomous Systems Seminar playlist: https://www.youtube.com/playlist?list=PLoROMvodv4rMeercb-kvGLUrOq4HR6BZD ► Check out the entire catalog of courses and programs available through Stanford Online: https://online.stanford.edu/explore View our Robotics and Autonomous Systems Graduate Certificate: https://online.stanford.edu/programs/robotics-and-autonomous-systems-graduate-certificate