Panel: Generalization in reinforcement learning

Speakers: Mingfei Sun, Researcher, Microsoft Research Cambridge Roberta Raileanu, PhD Student, NYU Wendelin Böhmer, Assistant Professor, Delft University of Technology Harm van Seijen, Principal Research Manager, Microsoft Research Montreal Cheng Zhang, Principal Researcher, Microsoft Research Cambridge The ability for a reinforcement learning (RL) policy to generalize is a key requirement for the broad application of RL algorithms. This generalization ability is also essential to the future of RL—both in theory and in practice. Join Microsoft researchers Harm van Seijen, Cheng Zhang, and Mingfei Sun, along with Dr. Wendelin Boehmer from Delft University of Technology and Dr. Roberta Raileanu from New York University, as they examine how agents struggle to transfer learned policies to new environments or tasks and explore why generalization remains challenging for state-of-the-art deep RL algorithms. In addition, they will discuss open questions about the right way to think about ge