Recent Progress in Continuous-Time Reinforcement Learning and Regret Analysis

Explore recent advancements in continuous-time reinforcement learning and regret analysis through this 53-minute lecture delivered by Xin Guo at the Centre International de Rencontres Mathématiques in Marseille, France. Recorded during the "Advances in Stochastic Control and Optimal Stopping with Applications in Economics and Finance" meeting on September 13, 2022, this talk offers valuable insights into the field of mathematical optimization. Delve into the complexities of continuous-time reinforcement learning and gain a deeper understanding of regret analysis techniques. Access this enriched video content through CIRM's Audiovisual Mathematics Library or carmin.tv, where you can utilize features such as chapter markers, keywords, abstracts, and bibliographies to enhance your learning experience.

Xin Guo: Some recent progress in continuous-time reinforcement learning and regret analysis