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Introduction

  • Harold J. Kushner
  • Paul G. Dupuis
Part of the Applications of Mathematics book series (SMAP, volume 24)

Abstract

This book is concerned with numerical methods for stochastic control and optimal stochastic control problems. The random process models of the controlled or uncontrolled stochastic systems are either diffusions or jump diffusions. Stochastic control is a very active area of research and new problem formulations and sometimes surprising applications appear regularly. We have chosen forms of the models which cover the great bulk of the formulations of the continuous time stochastic control problems which have appeared to date. The standard formats are covered, but much emphasis is given to the newer and less well known formulations. The controlled process might be either stopped or absorbed on leaving a constraint set or upon first hitting a target set, or it might be reflected or “projected” from the boundary of a constraining set. In some of the more recent applications of the reflecting boundary problem, for example the so-called heavy traffic approximation problems, the directions of reflection are actually discontinuous. In general, the control might be representable as a bounded function or it might be of the so-called impulsive or singular control types. Both the “drift” and the “variance” might be controlled. The cost functions might be any of the standard types: Discounted, stopped on first exit from a set, finite time, optimal stopping, average cost per unit time over the infinite time interval, and so forth. There might be separate costs when the process is on the boundary and when it is in the interior of the set of interest. In fact all of the standard cost functionals can be dealt with by the methods to be presented. There is a close connection between approximation methods for stochastic control and those for optimal nonlinear filtering, and approximation methods for the latter problem are also discussed.

Keywords

Optimal Control Problem Stochastic Control Jump Diffusion Singular Control Deterministic Problem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag New York, Inc. 1992

Authors and Affiliations

  • Harold J. Kushner
    • 1
  • Paul G. Dupuis
    • 1
  1. 1.Division of Applied MathematicsBrown UniversityProvidenceUSA

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