Stochastic Optimal Control in Infinite Dimension Dynamic Program
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 op
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Giorgio Fabbri Fausto Gozzi Andrzej Święch
Stochastic Optimal Control in Infinite Dimension Dynamic Programming and HJB Equations With a Contribution by Marco Fuhrman and Gianmario Tessitore
Probability Theory and Stochastic Modelling Volume 82
Editors-in-chief Søren Asmussen, Aarhus, Denmark Peter W. Glynn, Stanford, CA, USA Yves Le Jan, Orsay, France Advisory Board Martin Hairer, Coventry, UK Peter Jagers, Gothenburg, Sweden Ioannis Karatzas, New York, NY, USA Frank P. Kelly, Cambridge, UK Andreas Kyprianou, Bath, UK Bernt Øksendal, Oslo, Norway George Papanicolaou, Stanford, CA, USA Etienne Pardoux, Marseille, France Edwin Perkins, Vancouver, BC, Canada Halil Mete Soner, Zürich, Switzerland
The Probability Theory and Stochastic Modelling series is a merger and continuation of Springer’s two well established series Stochastic Modelling and Applied Probability and Probability and Its Applications series. It publishes research monographs that make a significant contribution to probability theory or an applications domain in which advanced probability methods are fundamental. Books in this series are expected to follow rigorous mathematical standards, while also displaying the expository quality necessary to make them useful and accessible to advanced students as well as researchers. The series covers all aspects of modern probability theory including • • • • • •
Gaussian processes Markov processes Random fields, point processes and random sets Random matrices Statistical mechanics and random media Stochastic analysis
as well as applications that include (but are not restricted to): • Branching processes and other models of population growth • Communications and processing networks • Computational methods in probability and stochastic processes, including simulation • Genetics and other stochastic models in biology and the life sciences • Information theory, signal processing, and image synthesis • Mathematical economics and finance • Statistical methods (e.g. empirical processes, MCMC) • Statistics for stochastic processes • Stochastic control • Stochastic models in operations research and stochastic optimization • Stochastic models in the physical sciences
More information about this series at http://www.springer.com/series/13205
Giorgio Fabbri Fausto Gozzi Andrzej Święch •
Stochastic Optimal Control in Infinite Dimension Dynamic Programming and HJB Equations With a Contribution by Marco Fuhrman and Gianmario Tessitore
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Giorgio Fabbri Aix-Marseille School of Economics CNRS, Aix-Marseille University, EHESS, Centrale Marseille Marseille France
Andrzej Święch School of Mathematics Georgia Institute of Technology Atlanta, GA USA
Fausto Gozzi Dipartimento di Economia e Finanza Università LUISS – Guido Carli Rome Italy
ISSN 2199-3130 ISSN 2199-3149 (electronic) Probability Theory and Stochastic Modelling ISBN 978-3-319-53066-6 ISBN 978-3-319-53067-3 (eBook) DOI 10.1007/978-3-319-53067-3 Library of Congress Control Number: 2017934613 Mathematics Subject Classification (2010): 49Lxx, 93E20, 49L20, 35R15, 3
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