LINMA2222 Stochastic optimal control and reinforcement learning, Fall 2026
Main themes
- Part 1: Foundations of probabilities, system, and optimal control
- Part 2: Exact algorithms for optimal decision-making and control
- Part 3: Approximate algorithms
- Part 4: Data-driven optimal decision-making and control, and applications
Teaching material
- Control Systems and Reinforcement Learning by Sean Meyn, Cambridge University Press, 2022
- Homework assignments, slides, summaries available on Moodle
Evaluation
- Homework exercises of project-type nature
- An oral exam, during which the homework will be discussed
Other resources
CC BY-SA 4.0 Guillaume Berger.
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