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Titlebook: Optimization of Stochastic Discrete Systems and Control on Complex Networks; Computational Networ Dmitrii Lozovanu,Stefan Pickl Book 2015 S

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書目名稱Optimization of Stochastic Discrete Systems and Control on Complex Networks
副標(biāo)題Computational Networ
編輯Dmitrii Lozovanu,Stefan Pickl
視頻videohttp://file.papertrans.cn/704/703295/703295.mp4
概述Systematizes the most important existing methods of stochastic dynamic optimization.Describes new algorithms for solving different classes of stochastic dynamic programming problems.Presents methods t
叢書名稱Advances in Computational Management Science
圖書封面Titlebook: Optimization of Stochastic Discrete Systems and Control on Complex Networks; Computational Networ Dmitrii Lozovanu,Stefan Pickl Book 2015 S
描述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.
出版日期Book 2015
關(guān)鍵詞Complex networks; Discrete optimal control; Game theory; Linear programming; Markov decision process; Sto
版次1
doihttps://doi.org/10.1007/978-3-319-11833-8
isbn_softcover978-3-319-35873-4
isbn_ebook978-3-319-11833-8Series ISSN 1388-4301
issn_series 1388-4301
copyrightSpringer International Publishing Switzerland 2015
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Stochastic Optimal Control Problems and Markov Decision Processes with Infinite Time Horizon,The aim of this chapter is to develop methods and algorithms for determining the optimal solutions of stochastic discrete control problems and Markov decision problems with an infinite time horizon.
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A Game-Theoretical Approach to Markov Decision Processes, Stochastic Positional Games and MulticritIn this chapter we formulate and study a class of stochastic positional games applying the game-theoretical concept to Markov decision problems with average and expected total discounted costs optimization criteria.
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Dynamic Programming Algorithms for Finite Horizon Control Problems and Markov Decision Processes,In this chapter we study stochastic discrete control problems and Markov decision processes with finite time horizon. We assume that the set of states of dynamical system is finite and the starting and the final states are fixed.
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