Stochastic optimal control in infinite dimension : dynamic programming and HJB equations /

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Bibliographic Details
Author / Creator:Fabbri, Giorgio, author.
Imprint:Cham, Switzerland : Springer, 2017.
Description:1 online resource
Language:English
Series:Probability theory and stochastic modelling ; 82
Probability theory and stochastic modelling ; v. 82.
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/11308376
Hidden Bibliographic Details
Other authors / contributors:Gozzi, Fausto, author.
Święch, Andrezej, author.
ISBN:9783319530673
3319530674
9783319530666
3319530666
9783319530680
3319530682
9783319850535
3319850539
Digital file characteristics:PDF
text file
Notes:Includes bibliographical references and index.
Vendor-supplied metadata.
Summary:Providing an introduction to stochastic optimal control in infinite dimension, this book gives a complete account of the theory of second-order HJB equations in infinite-dimensional Hilbert spaces, focusing on its applicability to associated stochastic optimal control problems. It features a general introduction to optimal stochastic control, including basic results (e.g. the dynamic programming principle) with proofs, and provides examples of applications. A complete and up-to-date exposition of the existing theory of viscosity solutions and regular solutions of second-order HJB equations in Hilbert spaces is given, together with an extensive survey of other methods, with a full bibliography. In particular, Chapter 6, written by M. Fuhrman and G. Tessitore, surveys the theory of regular solutions of HJB equations arising in infinite-dimensional stochastic control, via BSDEs. The book is of interest to both pure and applied researchers working in the control theory of stochastic PDEs, and in PDEs in infinite dimension. Readers from other fields who want to learn the basic theory will also find it useful. The prerequisites are: standard functional analysis, the theory of semigroups of operators and its use in the study of PDEs, some knowledge of the dynamic programming approach to stochastic optimal control problems in finite dimension, and the basics of stochastic analysis and stochastic equations in infinite-dimensional spaces.
Providing an introduction to stochastic optimal control in inαnite dimension, this book gives a complete account of the theory of second-order HJB equations in inαnite-dimensional Hilbert spaces, focusing on its applicability to associated stochastic optimal control problems. It features a general introduction to optimal stochastic control, including basic results (e.g. the dynamic programming principle) with proofs, and provides examples of applications. A complete and up-to-date exposition of the existing theory of viscosity solutions and regular solutions of second-order HJB equations in Hilbert spaces is given, together with an extensive survey of other methods, with a full bibliography. In particular, Chapter 6, written by M. Fuhrman and G. Tessitore, surveys the theory of regular solutions of HJB equations arising in inαnite-dimensional stochastic control, via BSDEs. The book is of interest to both pure and applied researchers working in the control theory of stochastic PDEs, and in PDEs in inαnite dimension. Readers from other αelds who want to learn the basic theory will also αnd it useful. The prerequisites are: standard functional analysis, the theory of semigroups of operators and its use in the study of PDEs, some knowledge of the dynamic programming approach to stochastic optimal control problems in αnite dimension, and the basics of stochastic analysis and stochastic equations in inαnite-dimensional spaces.
Other form:Print version: Fabbri, Giorgio. Stochastic optimal control in infinite dimension. Cham, Switzerland : Springer, 2017 3319530666 9783319530666
Standard no.:10.1007/978-3-319-53067-3