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Advances in Mechanics and Mathematics #14: Markov Decision Processes with Their Applications

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Synopses & Reviews

Publisher Comments:

Markov decision processes (MDPs), also called stochastic dynamic programming, were first studied in the 1960s. MDPs can be used to model and solve dynamic decision-making problems that are multi-period and occur in stochastic circumstances. There are three basic branches in MDPs: discrete-time MDPs, continuous-time MDPs and semi-Markov decision processes. Starting from these three branches, many generalized MDPs models have been applied to various practical problems. These models include partially observable MDPs, adaptive MDPs, MDPs in stochastic environments, and MDPs with multiple objectives, constraints or imprecise parameters. Markov Decision Processes With Their Applications examines MDPs and their applications in the optimal control of discrete event systems (DESs), optimal replacement, and optimal allocations in sequential online auctions. The book presents four main topics that are used to study optimal control problems: *a new methodology for MDPs with discounted total reward criterion; *transformation of continuous-time MDPs and semi-Markov decision processes into a discrete-time MDPs model, thereby simplifying the application of MDPs; *MDPs in stochastic environments, which greatly extends the area where MDPs can be applied; *applications of MDPs in optimal control of discrete event systems, optimal replacement, and optimal allocation in sequential online auctions. This book is intended for researchers, mathematicians, advanced graduate students, and engineers who are interested in optimal control, operation research, communications, manufacturing, economics, and electronic commerce.

Synopsis:

Markov Decision Processes With Their Applications examines MDPs and their applications in the optimal control of discrete event systems (DESs), optimal replacement, and optimal allocations in sequential online auctions. This book is intended for researchers, mathematicians, advanced graduate students, and engineers who are interested in optimal control, operation research, communications, manufacturing, economics, and electronic commerce.

Synopsis:

Put together by two top researchers in the Far East, this text examines Markov Decision Processes - also called stochastic dynamic programming - and their applications in the optimal control of discrete event systems, optimal replacement, and optimal allocations in sequential online auctions. This dynamic new book offers fresh applications of MDPs in areas such as the control of discrete event systems and the optimal allocations in sequential online auctions.

Table of Contents

List of Figures.- List of Tables.- Preface.- Acknowledgments.- 1. Introduction.- 2. Discrete-Time Markov Decision Processes: Total Reward.- 3. Discrete-Time Markov Decision Processes: Average Criterion.- 4. Continuous-Time Markov Decision Processes.- 5. Semi-Markov Decision Processes.- 6. Markov Decision Processes in Semi-Markov Environments.- 7. Optimal Control of Discrete Event Systems: I. 8. Optimal Control of Discrete Event Systems: II.- 9. Optimal Replacement Under Stochastic Environments.- 10. Optimal Allocation in Sequential Online Auctions.- Index.

Product Details

ISBN:
9780387369501
Author:
Hu, Qiying
Publisher:
Springer
Author:
Yue, Wuyi
Subject:
Linear Programming
Subject:
Engineering - Industrial
Subject:
Probability & Statistics - General
Subject:
Industrial engineering
Subject:
Operations Research
Subject:
decision making problems
Subject:
decision processes
Subject:
discrete event systems
Subject:
Stochastic dynamic programming
Subject:
Operations Research, Management Science
Subject:
Probability Theory and Stochastic Processes
Subject:
Calculus of Variations and Optimal Control; Optimization
Subject:
Industrial and Production Engineering
Subject:
Industrial and Production Engineering <P>MDPs have been applied in many areas, such as communications, signal processing, artificial intelligence, stochastic scheduling and manufacturing systems, discrete event systems, management and economies. This book
Subject:
Mathematics-Computer
Copyright:
Edition Description:
Book
Series:
Advances in Mechanics and Mathematics
Series Volume:
14
Publication Date:
20071126
Binding:
HARDCOVER
Language:
English
Illustrations:
Y
Pages:
314
Dimensions:
235 x 155 mm 1370 gr

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Advances in Mechanics and Mathematics #14: Markov Decision Processes with Their Applications New Hardcover
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$180.25 In Stock
Product details 314 pages Springer - English 9780387369501 Reviews:
"Synopsis" by , Markov Decision Processes With Their Applications examines MDPs and their applications in the optimal control of discrete event systems (DESs), optimal replacement, and optimal allocations in sequential online auctions. This book is intended for researchers, mathematicians, advanced graduate students, and engineers who are interested in optimal control, operation research, communications, manufacturing, economics, and electronic commerce.
"Synopsis" by , Put together by two top researchers in the Far East, this text examines Markov Decision Processes - also called stochastic dynamic programming - and their applications in the optimal control of discrete event systems, optimal replacement, and optimal allocations in sequential online auctions. This dynamic new book offers fresh applications of MDPs in areas such as the control of discrete event systems and the optimal allocations in sequential online auctions.
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