Stanford AA203: Optimal and Learning-Based Control Course Materials
caglar_ee · x · 2026-08-12
Stanford University has released video lectures and materials for the Spring 2026 course AA203: Optimal and Learning-Based Control, taught by Marco Pavone and Daniele Gammelli.
The course covers optimal control techniques for systems with known and unknown dynamics. Key topics include:
- Dynamic programming and Hamilton-Jacobi reachability
- Direct and indirect methods for trajectory optimization, and model predictive control (MPC)
- Adaptive control, model-based and model-free reinforcement learning
- Connections between modern reinforcement learning and fundamental optimal control
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