Introduction to Multi-Armed Bandits - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Introduction to Multi-Armed Bandits write by Aleksandrs Slivkins. This book was released on 2019-10-31. Introduction to Multi-Armed Bandits available in PDF, EPUB and Kindle. 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 book to provide a textbook like treatment of the subject.
Introduction to Multi-Armed Bandits
Introduction to Multi-Armed Bandits - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Introduction to Multi-Armed Bandits write by Aleksandrs Slivkins. This book was released on 2019. Introduction to Multi-Armed Bandits available in PDF, EPUB and Kindle. 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 book to provide a textbook like treatment of the subject.
Bandit Algorithms
Bandit Algorithms - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Bandit Algorithms write by Tor Lattimore. This book was released on 2020-07-16. Bandit Algorithms available in PDF, EPUB and Kindle. A comprehensive and rigorous introduction for graduate students and researchers, with applications in sequential decision-making problems.
Multi-armed Bandit Allocation Indices
Multi-armed Bandit Allocation Indices - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Multi-armed Bandit Allocation Indices write by John Gittins. This book was released on 2011-02-18. Multi-armed Bandit Allocation Indices available in PDF, EPUB and Kindle. 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 of sequential resource allocation and stochastic scheduling problems. Since then there has been a remarkable flowering of new insights, generalizations and applications, to which Glazebrook and Weber have made major contributions. This second edition brings the story up to date. There are new chapters on the achievable region approach to stochastic optimization problems, the construction of performance bounds for suboptimal policies, Whittle's restless bandits, and the use of Lagrangian relaxation in the construction and evaluation of index policies. Some of the many varied proofs of the index theorem are discussed along with the insights that they provide. Many contemporary applications are surveyed, and over 150 new references are included. Over the past 40 years the Gittins index has helped theoreticians and practitioners to address a huge variety of problems within chemometrics, economics, engineering, numerical analysis, operational research, probability, statistics and website design. This new edition will be an important resource for others wishing to use this approach.
Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems
Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems write by Sébastien Bubeck. This book was released on 2012. Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems available in PDF, EPUB and Kindle. 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 payoffs and adversarial payoffs. Besides the basic setting of finitely many actions, it analyzes some of the most important variants and extensions, such as the contextual bandit model.
