LINMA2725 Stochastic Optimal Control and Reinforcement Learning Fall 2024

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

• Slides of Part 4.1

• Slides of Part 4.2

• Slides of Part 4.3

• Slides of Part 4.4