Covers deep reinforcement learning techniques for continuous control, focusing on proximal policy optimization methods and their advantages over standard policy gradient approaches.
Explores deep learning for autonomous vehicles, covering perception, action, and social forecasting in the context of sensor technologies and ethical considerations.
