Princeton Robotics Seminar - Dynamic Game Models for Multi-Agent Interactions: The Role of Information in Designing Efficient Algorithms
Bio: David Fridovich-Keil is an assistant professor at the University of Texas at Austin. David’s research spans optimal control, dynamic game theory, learning for control, and robot safety. While he has also worked on problems in distributed control, reinforcement learning, and active search, he is currently investigating the role of dynamic game theory in multi-agent interactive settings such as traffic. David’s work also focuses on the interplay between machine learning and classical ideas from robust, adaptive, and geometric control theory.