OUTLINE OF COURSE II
- Week 1. Introduction expected utility. Preference axioms and expected utility, risk aversion. Gollier, Chapters 1-2.
- Week 2. Applications: the equity premium, and one and multi-period investment problems. Gollier, Chapters 3, 4, 9.
- Week 3. Problems with the real world: violations of expected utility. Prospect Theory and Regret Theory.
- Week 4. Catch up.
- Week 5. Basics of RL. Chapters 1-3, Sutton and Barto.
- Week 6. Dynamic Programming. Chapter 4, Sutton and Barto.
- Week 7. More DP and Monte Carlo Methods. Chapter 5, Sutton and Barto.
- Week 8. TD Learning. Chapter 6, Sutton and Barto.
- Week 9. Function Approximation and Neural Networks. Chapter 8, Sutton and Barto.
- Week 10. Inference and Bayesian Statistics. Chapters 2-3, MacKay.
- Week 11. Learning as Inference. Chapters 20-22, 41, MacKay
- Week 12-13. In-class presentations.