9781627056380-1627056386-Multi-Armed Bandits: Theory and Applications to Online Learning in Networks (Synthesis Lectures on Communication Networks)

Multi-Armed Bandits: Theory and Applications to Online Learning in Networks (Synthesis Lectures on Communication Networks)

ISBN-13: 9781627056380
ISBN-10: 1627056386
Author: Zhao, Qing
Publication date: 2019
Publisher: Morgan & Claypool Publishers
Format: Paperback 166 pages
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Book details

ISBN-13: 9781627056380
ISBN-10: 1627056386
Author: Zhao, Qing
Publication date: 2019
Publisher: Morgan & Claypool Publishers
Format: Paperback 166 pages

Summary

Acknowledged authors Zhao, Qing wrote Multi-Armed Bandits: Theory and Applications to Online Learning in Networks (Synthesis Lectures on Communication Networks) comprising 166 pages back in 2019. Textbook and eTextbook are published under ISBN 1627056386 and 9781627056380. Since then Multi-Armed Bandits: Theory and Applications to Online Learning in Networks (Synthesis Lectures on Communication Networks) textbook was available to sell back to BooksRun online for the top buyback price or rent at the marketplace.

Description

Multi-armed bandit problems pertain to optimal sequential decision making and learning in unknown environments.

Since the first bandit problem posed by Thompson in 1933 for the application of clinical trials, bandit problems have enjoyed lasting attention from multiple research communities and have found a wide range of applications across diverse domains. This book covers classic results and recent development on both Bayesian and frequentist bandit problems. We start in Chapter 1 with a brief overview on the history of bandit problems, contrasting the two schools--Bayesian and frequentis --of approaches and highlighting foundational results and key applications. Chapters 2 and 4 cover, respectively, the canonical Bayesian and frequentist bandit models. In Chapters 3 and 5, we discuss major variants of the canonical bandit models that lead to new directions, bring in new techniques, and broaden the applications of this classical problem. In Chapter 6, we present several representative application examples in communication networks and social-economic systems, aiming to illuminate the connections between the Bayesian and the frequentist formulations of bandit problems and how structural results pertaining to one may be leveraged to obtain solutions under the other.

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