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This course explores how to effectively predict the actions of other agents in the design of autonomous systems. Students will learn about reachable sets computed using dynamic game formulations, game-theoretic motion planning, feedback Nash equilibrium strategies, and behavioral models with real-time learned parameters. The teaching method includes theoretical concepts, demonstrations on simulations, and robotic experiments. The course is intended for individuals interested in robotics, autonomous systems, and game theory.
