Reinforcement learning problems involve learning what to do-how to map situations to actions-so as to maximize a numerical reward signal. Introduces the theory and practice of modern reinforcement learning. The course will cover model-free and model-based reinforcement learning methods, especially those based on temporal difference learning and policy gradient algorithms. This course introduces the theory and practice of modern reinforcement learning.
