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Restless Multi-Armed Bandit in Oppor...
~
Chen, Lin.
Restless Multi-Armed Bandit in Opportunistic Scheduling
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Restless Multi-Armed Bandit in Opportunistic Scheduling/ by Kehao Wang, Lin Chen.
Author:
Wang, Kehao.
other author:
Chen, Lin.
Description:
XII, 151 p. 12 illus. in color.online resource. :
Contained By:
Springer Nature eBook
Subject:
Electrical engineering. -
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. - 1st ed. 2021. - XII, 151 p. 12 illus. in color.online resource.
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:
596380
Electrical engineering.
LC Class. No.: TK1-9971
Dewey Class. No.: 621.382
Restless Multi-Armed Bandit in Opportunistic Scheduling
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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.
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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.
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