Hybrid Reward Architecture

成立: 2020年5月29日

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.

成立: 2017年7月7日

The Reinforcement Learning research group works on theoretical foundations, algorithms, and systems for autonomous decision making. Our main research areas include exploration-exploitation trade-offs, off-policy learning, and generalization for contextual bandits, Markov decision processes, and contextual decision processes.