Optimization of Stochastic Discrete Systems and Control on Complex Networks: Computational Networks: 12 (Advances in Computational Management Science) - Tapa blanda

Lozovanu, Dmitrii; Pickl, Stefan

9783319358734: Optimization of Stochastic Discrete Systems and Control on Complex Networks: Computational Networks: 12 (Advances in Computational Management Science)

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ISBN 10: 3319358731 ISBN 13: 9783319358734

Editorial: Springer, 2016

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“This book contributes to the systematization of the most relevant existing methods for these problems by introducing new algorithms for solving different classes of stochastic dynamic programming problems. ... The mathematical and computational level of the book will enable students and practitioners to deepen their understanding of the topic. Numerous examples are included to illustrate the proposed algorithms and methods.” (Rosario Romera, Mathematical Reviews, July, 2015)

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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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EditorialSpringer
A�o de publicaci�n2016
ISBN 10 3319358731
ISBN 13 9783319358734
Encuadernaci�nTapa blanda
IdiomaIngl�s
N�mero de p�ginas424

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9783319118321: Optimization of Stochastic Discrete Systems and Control on Complex Networks: Computational Networks: 12 (Advances in Computational Management Science)

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ISBN 10: 3319118323 ISBN 13: 9783319118321
Editorial: Springer, 2014
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Optimization of Stochastic Discrete Systems and Control on Complex Networks

Dmitrii Lozovanu|Stefan Pickl

Publicado por Springer International Publishing, 2016

ISBN 10: 3319358731 ISBN 13: 9783319358734

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Librería: moluna, Greven, Alemania

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Condici�n: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Systematizes the most important existing methods of stochastic dynamic optimizationDescribes new algorithms for solving different classes of stochastic dynamic programming problemsPresents methods to solve practical decision problems from d. N� de ref. del art�culo: 385703943

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Optimization of Stochastic Discrete Systems and Control on Complex Networks

Stefan Pickl

Publicado por Springer International Publishing Sep 2016, 2016

ISBN 10: 3319358731 ISBN 13: 9783319358734

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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania

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Taschenbuch. Condici�n: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 424 pp. Englisch. N� de ref. del art�culo: 9783319358734

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

Stefan Pickl

Publicado por Springer International Publishing, 2016

ISBN 10: 3319358731 ISBN 13: 9783319358734

Nuevo Taschenbuch

Librería: AHA-BUCH GmbH, Einbeck, Alemania

Calificaci�n del vendedor: 5 de 5 estrellas

Taschenbuch. Condici�n: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. N� de ref. del art�culo: 9783319358734

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