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Titlebook: Finite Approximations in Discrete-Time Stochastic Control; Quantized Models and Naci Saldi,Tamás Linder,Serdar Yüksel Book 2018 Springer In

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书目名称Finite Approximations in Discrete-Time Stochastic Control
副标题Quantized Models and
编辑Naci Saldi,Tamás Linder,Serdar Yüksel
视频video
概述Demonstrates how quantization can be used to systematically optimize decentralized stochastic control problems.Explores network control applications.Provides a framework for comparing approximation mo
丛书名称Systems & Control: Foundations & Applications
图书封面Titlebook: Finite Approximations in Discrete-Time Stochastic Control; Quantized Models and Naci Saldi,Tamás Linder,Serdar Yüksel Book 2018 Springer In
描述In a unified form, this monograph presents fundamental results on the approximation of centralized and decentralized stochastic control problems, with uncountable state, measurement, and action spaces. It demonstrates how quantization provides a system-independent and constructive method for the reduction of a system with Borel spaces to one with finite state, measurement, and action spaces. In addition to this constructive view, the book considers both the information transmission approach for discretization of actions, and the computational approach for discretization of states and actions. Part I of the text discusses Markov decision processes and their finite-state or finite-action approximations, while Part II builds from there to finite approximations in decentralized stochastic control problems. .This volume is perfect for researchers and graduate students interested in stochastic controls. With the tools presented, readers will be able to establish the convergence of approximation models to original models and the methods are general enough that researchers can build corresponding approximation results, typically with no additional assumptions..
出版日期Book 2018
关键词stochastic control; decentralized stochastic control; quantization; numerical approximation; finite stat
版次1
doihttps://doi.org/10.1007/978-3-319-79033-6
isbn_softcover978-3-030-07710-5
isbn_ebook978-3-319-79033-6Series ISSN 2324-9749 Series E-ISSN 2324-9757
issn_series 2324-9749
copyrightSpringer International Publishing AG, part of Springer Nature 2018
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