Optimization of Stochastic Discrete Systems and Control on Complex Networks

Computational Networks de

,

Éditeur :

Springer


Collection :

Advances in Computational Management Science

Paru le : 2014-11-27

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Description
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.
Pages
400 pages
Collection
Advances in Computational Management Science
Parution
2014-11-27
Marque
Springer
EAN papier
9783319118321
EAN EPUB
9783319118338

Informations sur l'ebook
Nombre pages copiables
4
Nombre pages imprimables
40
Taille du fichier
9114 Ko
Prix
94,94 €