Model Predictive Control and Reinforcement Learning

Block Course, 06.10.2025 - 10.10.2025, 9:00-18:00


Lecturers: Prof. Dr. Joschka Boedecker (Uni Freiburg), Prof. Dr. Moritz Diehl (Uni Freiburg), Prof. Dr. Sebastien Gros (NTNU Trondheim)

Exercises: Leonard Fichtner, Andrea Ghezzi and Jasper Hoffmann


Contacts: for any questions feel free to contact us mpcrl@cs.uni-freiburg.de.


Locations: Kollegiengebäude I, HS 1199, Platz der Universität 3, 79098 Freiburg, Google Maps


Event announcement: MPCRL25

Download our flyer and feel free to share it!


Preliminary timetable

JB: Joschka Boedecker, MD: Moritz Diehl, SG: Sebastien Gros, LF: Leonard Fichtner, AG: Andrea Ghezzi, JH: Jasper Hoffmann

 Monday 6.10.Tuesday 7.10.Wednesday 8.10.Thursday 9.10.Friday 10.10.
9:00Lecture 1 - Introduction to RL (JB)
Markov Decision Process, Dynamic Programming, Bellman equation, Value function, Q function, Policy and value iteration
Lecture 4 (MD)
MPC cont’d from linear to nonlinear MPC; sensitivity computation and implicit function theorem
Lecture 6 - Synthesis of MPC and RL (SG)
Overview over Synthesis of MPC and RL
Lecture 8 (SG)
RL + MPC Why does it work?
Lecture 10 (SG)
AI for Decision Making
10:30Coffee Break
11:00Lecture 2 - Introduction to Optimal Control (MD)
Parallelism between DP and LQR; introduction to MPC; basics of numerical optimization for control
Exercise
Acados interface + basic MPC with acados + DiffMPC layer with leap-c
Lecture 7 - An MPC prior for SAC (JH, LF)
Integrating MPC into actor-critic methods with leap-c
Project Work / TutorialsProject presentation
12:30Lunch Break
14:00Lecture 3 - Actor-Critic Methods (JB)
Temporal Difference, Actor-Critic Methods, Soft Actor-Critic
Lecture 5 (MD, AG, JH)
Imitation Learning from MPC
Exercise
MPC prior for SAC using leap-c
Lecture 9
TBA
Project presentation
15:30Coffee Break
16:00 - 17:30Exercise
Basics in PyTorch and Actor Critic methods
Exercise
Imitation learning + Q&A on software
Project Work / TutorialsProject Work / TutorialsFree
17:30Project Pitches
19:00Welcome reception Dinner with participants  

 

 

 

Course topics (may be subject to updates)

  • Dynamic Programming (DP) concepts and algorithms - value iteration and policy iteration
  • Linear Quadratic Regulator (LQR) and Riccati equations
  • Dynamic Systems: Simulation and Optimal Control 
  • Markov Decision Processes (MDP)
  • Reinforcement Learning (RL) formulations and approaches  
  • Nonlinear Model Predictive Control
  • When to use RL in MPC?
  • Differentiable MPC within Actor-Critic methods
  • Closed-loop tuning of MPC with RL
  • Overview of possible synergies between MPC and RL

 

A more detailed program will be shared soon!


Registration is open!

For registering, please complete this form

Registration deadline: within August 31, 2025, until the limit of 60 participants is reached (first come first served). 

Participation fee: 400 EUR (free of charge for master’s students from the University of Freiburg). The fee includes coffee breaks during the event, a welcome reception, and a dinner with the participants. 

Cancellation policy: no refund possible.

Registration for master students of Uni Freiburg is free of charge, please fill this form: UFR student registration


Please note that your registration will be considered complete only after we have received your payment. You will receive bank transfer details via email shortly after submitting your registration form. As registrations are processed manually, please allow some time before receiving your confirmation email.


Targeted audience

This block course is intended for master students and PhD students from engineering, computer science, mathematics, physics, and other mathematical sciences. 

For interested Master students:

  • We accept registration only from master students from the University of Freiburg
  • We strongly recommend the students to have taken at least two of the following courses: Numerical Optimization (Diehl, 6 ECTS), Numerical Optimal Control (Diehl, 6 ECTS), and Reinforcement Learning (Boedecker, 6 ECTS)
  • The evaluation of the course will be based on the exercise sessions and the project works. Further details on evaluation will be published soon.

Formal requirements

Relevant only for students of the university of Freiburg.

In order to receive 3 ECTS for this course, students need to pass all of the following:

  • Studienleistung (SL, ungraded)
    • Participation in the exercise session
  • Prüfungsleistung (PL, graded)
    • Project report

Every student from the University of Freiburg needs to fill out the registration form.

Please also read the project instructions from above.

On the first day (October 6th), students further need to decide whether they want to commit themselves to do the PL. The registration will take via the PL registration form below.