Deep Reinforcement Learning

Reinforcement Learning (RL), as a branch of machine learning focuses on goal-directed learning from interactions and sequential decision making in complex, dynamic, and uncertain environments. Potential applications of RL are diverse and include applications in areas of robotics, transportation, game playing, healthcare, psychology, neuroscience, industrial process control, and business management, to name a few. This course focuses on RL with function approximation by deep artificial neural networks (Deep RL). Students will learn about the recent advances in the field, including a wide range of deep RL methods, their applicability to different scenarios, their strengths, and their limitations.