Harold Kushner, Paul G. Dupuis

Numerical Methods for Stochastic Control Problems in Continuous Time (eBook, PDF)

• Format: PDF

Produktbeschreibung

Stochastic control is a very active area of research and this monograph written by two leading authorities in the field has been updated to reflect the latest developments. It covers effective numerical methods for stochastic control problems in continuous time on two levels, that of practice (algorithms and applications) and that of the mathematical development. It is broadly accessible for graduate students and researchers.

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Produktdetails

• Verlag: Springer US
• Seitenzahl: 476
• Erscheinungstermin: 27. November 2013
• Englisch
• ISBN-13: 9781461300076
• Artikelnr.: 44052709

Autorenporträt

Stochastic control is a very active area of research and this monograph written by two leading authorities in the field has been updated to reflect the latest developments. It covers effective numerical methods for stochastic control problems in continuous time on two levels, that of practice (algorithms and applications) and that of the mathematical development. It is broadly accessible for graduate students and researchers.

Inhaltsangabe

Review of Continuous Time Models.- Controlled Markov Chains.- Dynamic Programming Equations.- Markov Chain Approximation Method.- The Approximating Markov Chains.- Computational Methods.- The Ergodic Cost Problem.- Heavy Traffic and Singular Control.- Weak Convergence and the Characterization of Processes.- Convergence Proofs.- Convergence Proofs Continued.- Finite Time and Filtering Problems.- Controlled Variance and Jumps.- Problems from the Calculus of Variations: Finite Time Horizon.- Problems from the Calculus of Variations: Infinite Time Horizon.- The Viscosity Solution Approach.

Rezensionen

"The second edition of this acclaimed book from Springer-Verlag has the latest theoretical and practical information on solving stochastic control problems. Including proofs and algorithms using diffusion, jump-diffusion, and other process models, the authors help make randomness a little less scary."
Amazon.com Delivers Mathematics and Statistics e-bulletin, July 2001