Lecture 2: Planning and Learning

1. Preliminaries

2. Dynamic Programming

• Policy Iteration
• Value Iteration

3. Monte Carlo Methods

• MC Policy Evaluation (Prediction)
• MC Policy Optimization (Control)

4. Temporal Difference Learning

• TD Prediction
• TD Control: SARSA