Spring 2021 GRASP SFI: “Model-Based Deep RL for Robotics”
Abstract: Deep learning has shown promising results in robotics, but we are still far from having intelligent systems that can operate in the unstructured settings of the real world, where disturbances, variations, and unobserved factors lead to a dynamic environment. In the first part of the talk, I will show that model-based deep RL can […]