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Optimization of Stochastic Discrete Systems and Control on Complex Networks Computational Networks

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This book presents the latest findings on stochastic dynamic programming models and on solving optimal control problems in networks. It includes the authors’ new findings on determining the optimal solution of discrete optimal control problems in networks and on solving game variants of Markov decision problems in the context of computational networks. First, the book studies the finite state space of Markov processes and reviews the existing methods and algorithms for determining the main characteristics in Markov chains, before proposing new approaches based on dynamic programming and combinatorial methods. Chapter two is dedicated to infinite horizon stochastic discrete optimal control models and Markov decision problems with average and expected total discounted optimization criteria, while Chapter three develops a special game-theoretical approach to Markov decision processes and stochastic discrete optimal control problems. In closing, the book’s final chapter is devoted to finite horizon stochastic control problems and Markov decision processes. The algorithms developed represent a valuable contribution to the important field of computational network theory.

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Series Title

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Call Number

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Publisher

: Springer Cham., 2015

Collation

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Language

English

ISBN/ISSN

978-3-319-11833-8

Classification

NONE

Content Type

text

Media Type

computer

Carrier Type

online resource

Edition

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Subject(s)

Algorithms
Optimization
Discrete Optimization
Operations Research and Decision Theory
Operations Research
Management Science

Specific Detail Info

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Statement of Responsibility

Dmitrii Lozovanu, Stefan Pickl

Other Information

Cataloger

Yudi

Source

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