Lecture 1: Introduction to Reinforcement Learning

Lecture 2: Markov Decision Processes

Lecture 3: Planning by Dynamic Programming

Lecture 4: Model-Free Prediction

Lecture 5: Model-Free Control

Lecture 6: Value Function Approximation

Lecture 7: Policy Gradient Methods

Lecture 8: Integrating Learning and Planning

Lecture 9: Exploration and Exploitation

Lecture 10: Case Study: RL in Classic Games