TY  - BOOK
AU  - Lozovanu,Dmitrii
AU  - Pickl,Stefan
ED  - SpringerLink (Online service)
TI  - Optimization of Stochastic Discrete Systems and Control on Complex Networks: Computational Networks 
T2  - Advances in Computational Management Science,
SN  - 9783319118338
AV  - HD30.23 
U1  - 658.40301 23
PY  - 2015///
CY  - Cham
PB  - Springer International Publishing, Imprint: Springer
KW  - Economics
KW  - Computer software
KW  - Mathematical optimization
KW  - Operations research
KW  - Economics/Management Science
KW  - Operation Research/Decision Theory
KW  - Optimization
KW  - Operations Research, Management Science
KW  - Discrete Optimization
KW  - Algorithm Analysis and Problem Complexity
N1  - Discrete stochastic processes, numerical methods for Markov chains and polynomial time algorithms -- Stochastic optimal control problems and Markov decision processes with infinite time horizon -- A game-theoretical approach to Markov decision processes, stochastic positional games and multicriteria control models -- Dynamic programming algorithms for finite horizon control problems and Markov decision processes
N2  - 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
UR  - http://dx.doi.org/10.1007/978-3-319-11833-8
ER  -