Stochastic Optimal Control in Infinite Dimension - Worum geht es im Buch?

Stochastic Optimal Control in Infinite Dimension: Inhalt, Einordnung und bibliografische Details

Wer nach einem Buch von Giorgio Fabbri, Fausto Gozzi, Andrzej Święch, Marco Fuhrman, Gianmario Tessitore aus dem Themenfeld Sachbuch sucht, findet mit Stochastic Optimal Control in Infinite Dimension eine Ausgabe mit präziser inhaltlicher Positionierung. Der Untertitel Dynamic Programming and HJB Equations ergänzt den Haupttitel Stochastic Optimal Control in Infinite Dimension sinnvoll und gibt bereits früh einen konkreten Hinweis auf die inhaltliche Ausrichtung des Buches. Inhaltlich lässt sich Stochastic Optimal Control in Infinite Dimension folgendermaßen zusammenfassen: 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

Relevante Merkmale auf einen Blick

Wer Literatur aus dem Bereich Sachbuch sucht, findet in Stochastic Optimal Control in Infinite Dimension einen gut klassifizierbaren Titel. Auch das Veröffentlichungsdatum 2017 macht Stochastic Optimal Control in Infinite Dimension für zeitlich eingegrenzte Suchen besonders interessant. Stochastic Optimal Control in Infinite Dimension liegt in Deutsch vor, was für die inhaltliche Nutzung ebenso wichtig ist wie für die bibliografische Suche. Für alle, die Bücher von Giorgio Fabbri, Fausto Gozzi, Andrzej Święch, Marco Fuhrman, Gianmario Tessitore recherchieren oder vergleichen, ist Stochastic Optimal Control in Infinite Dimension eine relevante Ausgabe.

Thematische Einordnung von Stochastic Optimal Control in Infinite Dimension

Die Beschreibung zeigt, dass Stochastic Optimal Control in Infinite Dimension klar dem Bereich Sachbuch zugeordnet werden kann: 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 Ergänzend helfen die hinterlegten Schlagwörter dabei, Stochastic Optimal Control in Infinite Dimension thematisch schneller einzuordnen: Mathematical models, Probabilities, Stochastic processes, Control theory, Hilbert space, Mathematical optimization, Hamiltonian systems, Stochastic models, Geometry, infinitesimal, Hamilton-Jacobi equations

ISBN, Revision und weitere Referenzdaten

Sowohl die ISBN-10 3319530674 als auch die ISBN-13 9783319530673 erleichtern das Auffinden und Vergleichen dieser Ausgabe erheblich. Auch externe Referenzen sind vorhanden: Die Work-ID lautet OL20789497W, die zugehörigen Editions-IDs sind OL51662318M.

Die zentralen Metadaten zu Stochastic Optimal Control in Infinite Dimension

1. Thematische Tags: Mathematical models, Probabilities, Stochastic processes, Control theory, Hilbert space, Mathematical optimization, Hamiltonian systems, Stochastic models, Geometry, infinitesimal, Hamilton-Jacobi equations
2. Primäre Kategorie: Sachbuch
3. Untertitel: Dynamic Programming and HJB Equations
4. Internationale Standardbuchnummer (ISBN-13): 9783319530673
5. ISBN-10: 3319530674
6. Publiziert bei: Springer
7. Externe Editionsreferenzen: OL51662318M
8. Sprache: Deutsch
9. Open-Library-Work-ID: OL20789497W
10. Buchtitel: Stochastic Optimal Control in Infinite Dimension
11. Erscheinungsdatum: 2017
12. Kurzbeschreibung: 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
13. Verfasst von: Giorgio Fabbri, Fausto Gozzi, Andrzej Święch, Marco Fuhrman, Gianmario Tessitore

Auffindbarkeit und bibliografische Präzision

Stochastic Optimal Control in Infinite Dimension profitiert für die Auffindbarkeit besonders von der Verbindung zwischen Giorgio Fabbri, Fausto Gozzi, Andrzej Święch, Marco Fuhrman, Gianmario Tessitore, Sachbuch und den Tags Mathematical models, Probabilities, Stochastic processes, Control theory, Hilbert space, Mathematical optimization, Hamiltonian systems, Stochastic models, Geometry, infinitesimal, Hamilton-Jacobi equations, weil dadurch eine starke semantische Einordnung entsteht. Zusätzliche Präzision entsteht durch Identifikatoren wie 3319530674, 9783319530673 und OL20789497W, die die Ausgabe in verschiedenen Katalog- und Suchkontexten eindeutig referenzierbar machen.

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