Numerical Methods for Stochastic Control Problems in Continuous Time (Ima Volumes in Mathematics and Its Applications) - Hardcover
Book 3 of 30: Stochastic Modelling and Applied Probability
Synopsis
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 Finite Time Horizon.- Problems from the Calculus of Infinite Time Horizon.- The Viscosity Solution Approach.
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"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
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Numerical Methods for Stoachastic Control Problems in Continuous Time (Stochastic Modelling and Applied Probability)
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