Finite Approximations in Discrete-Time Stochastic Control

Naci Saldi

ISBN 10: 3030077101 / ISBN 13: 9783030077105

Published by Birkhäuser, Springer VS Jan 2019, 2019

About this Item

This item is printed on demand - Print on Demand Titel. Neuware -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.Springer Nature c/o IBS, Benzstrasse 21, 48619 Heek 208 pp. Englisch.

Seller Inventory # 9783030077105

Bibliographic Details

• Title: Finite Approximations in Discrete-Time Stochastic Control
• Publisher: Birkhäuser, Springer VS Jan 2019
• Publication Date: 2019
• Language: English
• ISBN 10: 3030077101
• ISBN 13: 9783030077105
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 155H x 12D millimeters 235 millimeters width by 155 millimeters height by 12 millimeters depth
• Weight: 324 grams

About this title

Synopsis

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.