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Restless multi-armed bandit in oppor...

Wang, Kehao.

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Restless multi-armed bandit in opportunistic scheduling

Record Type:	Electronic resources : Monograph/item
Title/Author:	Restless multi-armed bandit in opportunistic scheduling/ by Kehao Wang, Lin Chen.
Author:	Wang, Kehao.
other author:	Chen, Lin.
Published:	Cham :Springer International Publishing : : 2021.,
Description:	xii, 151 p. :ill., digital ;24 cm.
[NT 15003449]:	Introduction -- RMAB in Opportunistic Scheduling -- Optimality of Myopic Policy with Imperfect Sensing -- Whittle Index Policy with Imperfect Sensing -- Heuristic Policy with Imperfect Sensing -- Optimality of Myopic Policy with Imperfect Observation -- Whittle Index Policy for Multi-State Channel Scheduling -- Conclusion.
Contained By:	Springer Nature eBook
Subject:	Wireless communication systems - Mathematical models. -
Online resource:	https://doi.org/10.1007/978-3-030-69959-8
ISBN:	9783030699598

Restless multi-armed bandit in opportunistic scheduling
Wang, Kehao.

Restless multi-armed bandit in opportunistic scheduling[electronic resource] /by Kehao Wang, Lin Chen. - Cham :Springer International Publishing :2021. - xii, 151 p. :ill., digital ;24 cm.

Introduction -- RMAB in Opportunistic Scheduling -- Optimality of Myopic Policy with Imperfect Sensing -- Whittle Index Policy with Imperfect Sensing -- Heuristic Policy with Imperfect Sensing -- Optimality of Myopic Policy with Imperfect Observation -- Whittle Index Policy for Multi-State Channel Scheduling -- Conclusion.

This book provides foundations for the understanding and design of computation-efficient algorithms and protocols for those interactions with environment, i.e., wireless communication systems. The book provides a systematic treatment of the theoretical foundation and algorithmic tools necessarily in the design of computation-efficient algorithms and protocols in stochastic scheduling. The problems addressed in the book are of both fundamental and practical importance. Target readers of the book are researchers and advanced-level engineering students interested in acquiring in-depth knowledge on the topic and on stochastic scheduling and their applications, both from theoretical and engineering perspective. Introduces Restless Multi-Armed Bandit (RMAB) and presents its relevant tools involved in machine learning and how to adapt them for application; Elaborates on research bringing the conventional decision theory and stochastic optimal technology into wireless communication applications involving machine learning; Delivers a comprehensive treatment on problems ranging from theoretical modeling and analysis, to practical algorithm design and optimization.

ISBN: 9783030699598

Standard No.: 10.1007/978-3-030-69959-8doiSubjects--Topical Terms:

923148
Wireless communication systems
--Mathematical models.

LC Class. No.: TK5103.2 / .W36 2021

Dewey Class. No.: 621.3845

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300 $a xii, 151 p. : $b ill., digital ; $c 24 cm.
505 0 $a Introduction -- RMAB in Opportunistic Scheduling -- Optimality of Myopic Policy with Imperfect Sensing -- Whittle Index Policy with Imperfect Sensing -- Heuristic Policy with Imperfect Sensing -- Optimality of Myopic Policy with Imperfect Observation -- Whittle Index Policy for Multi-State Channel Scheduling -- Conclusion.
520 $a This book provides foundations for the understanding and design of computation-efficient algorithms and protocols for those interactions with environment, i.e., wireless communication systems. The book provides a systematic treatment of the theoretical foundation and algorithmic tools necessarily in the design of computation-efficient algorithms and protocols in stochastic scheduling. The problems addressed in the book are of both fundamental and practical importance. Target readers of the book are researchers and advanced-level engineering students interested in acquiring in-depth knowledge on the topic and on stochastic scheduling and their applications, both from theoretical and engineering perspective. Introduces Restless Multi-Armed Bandit (RMAB) and presents its relevant tools involved in machine learning and how to adapt them for application; Elaborates on research bringing the conventional decision theory and stochastic optimal technology into wireless communication applications involving machine learning; Delivers a comprehensive treatment on problems ranging from theoretical modeling and analysis, to practical algorithm design and optimization.
650 0 $a Wireless communication systems $x Mathematical models. $3 923148
650 0 $a Computer scheduling. $3 944065
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