A comprehensive and rigorous introduction for graduate students and researchers, with applications in sequential decision-making problems.

When looking for ways to improve your website, how do you decide which changes to make? And which changes to keep? This concise book shows you how to use Multia

Multi-armed bandits is a rich, multi-disciplinary area that has been studied since 1933, with a surge of activity in the past 10-15 years. This is the first boo

Decision-making in the face of uncertainty is a significant challenge in machine learning, and the multi-armed bandit model is a commonly used framework to addr

In this monograph, the focus is on two extreme cases in which the analysis of regret is particularly simple and elegant: independent and identically distributed