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

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

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

In 1989 the first edition of this book set out Gittins' pioneering index solution to the multi-armed bandit problem and his subsequent investigation of a wide o

The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intellig