MODUS Seminar Program

Weekly talks in the MODUS Seminar: Wednesday, 12:30-14:00, Room S102, FAN-B
Individual talks may be held via zoom or at different times, see the information, below.

Further talks will be announced as the semester progresses. To receive email notifications about upcoming talks, please subscribe to the MODUS elearning course.

Winter Semester 2026/2027

Friday, 9 October 2026, 10:00h, Room S 82 (NW II)
Sébastien Gros
Professor, Department of Engineering Cybernetics, NTNU Trondheim, Norway
Combining Reinforcement Learning and MPC - How to take optimal decisions with wrong models?

Abstract: Reinforcement Learning (RL) can be used to tune MPC schemes towards closed-loop optimality in the real world. That tuning is fundamentally different than using classical fitting approaches to adjust the model underlying MPC. These ideas are supported by a rich theory on how MPC is a universal approximation for Markov Decision Processes, provided that it is viewed in the right way. That theory proposes a bridge between the open-loop predictions of MPC and its closed-loop implementation. It also explains why using classical model fitting is sometimes good enough for achieving near-optimal closed-loop performance with MPC, and why it often falls short of achieving that. It finally opens a theoretical pathway on using (imperfect) simulation models to build optimal policies for the real-world, and on closing the “sim2real gap”. In this talk, we will provide an overview of these recent advances.

Further talks will be announced in the second half of October 2026