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Bandit Learning            cs    pitt

Books and tutorials

The Red Bible
N. Cesa-Bianchi, and G. Lugosi, Prediction, Learning, and Games.
Cambridge University Press, New York, 2006. ISBN 0521841089.
Table of Contents| Errata | Amazon
S. Bubeck and N. Cesa-Bianchi
Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems

In Foundations and Trends in Machine Learning, Vol 5: No 1, 1-122, 2012

[pdf] [Link to buy a book version]
Rémi Munos
The optimistic principle applied to games, optimization and planning: Towards foundations of Monte-Carlo Tree Search [Submitted to Foundations and Trends in Machine Learning]
Jean-Yves Audibert, Rémi Munos
ICML 2010 Tutorial on bandits [video]

Lectures

Nicolò Cesa-Bianchi
Bandit Algorithms for Online Linear Optimization
Gabor Lugosi
Adversarial bandit problems: the power of randomization
Kamalika Chaudhuri (UCSD)
CSE291W11
Andreas Krause (Caltech)
Caltech CS 101.2
Kamesh Munagala (Duke)
CPS296.04 Sequential Decision Theory: Algorithms, Policies, and Games