Recent Advances in Reinforcement Learning: From Foundations to Real-World Systems

Reinforcement Learning has long spread beyond computer science labs, becoming a central framework in the development of robotics, learning systems, and recently large language models. To discuss recent advances and foster exchange across sub-fields, we bring together experts from academia and industry working from the fundamentals of sequential decision-making and neuro-inspired mechanisms to the safe and scalable deployment of these techniques in real-world systems