Finite Approximations in Discrete-Time Stochastic Control : Quantized Models and Asymptotic Optimality. 1st ed. 2018

種類:

電子ブック

責任表示:

by Naci Saldi, Tamás Linder, Serdar Yüksel

出版情報:

Cham : Springer International Publishing : Imprint: Birkhäuser, 2018

著者名:

• Saldi, Naci.
• Linder, Tamás.
• Yüksel, Serdar.
• SpringerLink (Online service)

シリーズ名:

Systems & Control: Foundations & Applications ;

ISBN:

9783319790336 [3319790331]    

注記:

Introduction and Summary -- Part I: Finite Model Approximations in Stochastic Control -- Prelude to Part I -- Finite Action Approximation of Markov Decision Processes -- Finite-State Approximation of Markov Decision Processes -- Approximations for Partially Observed Markov Decision Processes -- Approximations for Constrained Markov Decision Problems -- Part II: Finite Model Approximations in Decentralized Stochastic Control -- Prelude to Part II -- Finite Model Approximations in Decentralized Stochastic Control -- Asymptotic Optimality of Finite Models for Specific Systems -- Index -- References.
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 mo

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