Spring 2020 GRASP Seminar Series: David Meger - February 28th, 2020

McGill University “Deep Reinforcement Learning of Robot Behaviors“ ABSTRACT Deep Reinforcement Learning (DRL) has great promise for learning behaviours flexibly, but can be hard to reproduce and require thousands of trials, which limits its practical use for robots. At McGill’s Mobile Robotics Lab, we have recently: Learned to swim with flippers in less than a dozen trials Reported reproducibility issues that changed the community’s empirical practices Developed TD3, continuous state/action DRL at world