Reinforcement Learning | Montréal

MSR Montréal focuses on improving the understanding of fundamental concepts in (deep) Reinforcement Learning (RL) and addressing the open problems that need to be overcome to employ RL on a large scale in the real world. For this reason, we work on challenges such as sample-efficiency, (systematic) generalization and robustness/safety of methods.