Handouts

• Basic facts from probability (a PDF file).

• More information about Normal (Gaussian) distribution: from MathWorld and from Wikipedia.

• Selecting an outcome according to a given probability distribution: this handout will help you to complete Assignment 1.

• A solution of the gambler's problem using the policy iteration algorithm: Example 4.3 from the text-book. This C program was written by Wee Pham.

• A solution of the Blackjack game using the on-policy Monte Carlo algorithm: This C program was written by Wee Pham.

• Frequently Asked Questions about Reinforcement Learning

• Reinforcement learning, a brief review paper written by Peter Dayan & Watkins, CJCH (2001). Published in: Encyclopedia of Cognitive Science London, England: MacMillan Press.

• Reinforcement Learning: A Survey, by Kaelbling, L.P., Littman, M.L., and Moore, A.W. Journal of Artificial Intelligence Research (1996), Volume 4, pages 237-285.

• Reinforcement Learning by Peter Dayan. A detailed overview of the basic theory underlying reinforcement learning, and its links with neuroscience, psychology, statistics and engineering. Published in CR Gallistel (editor), Steven's Handbook of Experimental Psychology, New York, NY: Wiley.