Control Theory and Reinforcement Learning

Control theory and reinforcement learning converge on a shared objective: facilitating autonomous, real-time decision-making to optimise dynamical processes. Historically, these disciplines have diverged in assumptions regarding available prior information and in analytical techniques applied. However, recent advances bridging the two domains are fostering collaborations. The upcoming CWI semester program in spring 2025, themed "Control Theory and Reinforcement Learning: Connections and Challenges", will comprise a spring school and workshops on various sub-topics, orchestrated by a distinguished team including Sean Meyn, Bert Kappen, Maryam Kamgarpour, Frans Oliehoek, Debabrota Basu, Matthia Sabatelli, and Aditya Gilra, to explore the intersections and challenges within these intertwined fields.