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Martingale problems for controlled processes

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Stochastic Modelling and Filtering

Part of the book series: Lecture Notes in Control and Information Sciences ((LNCIS,volume 91))

Abstract

Martingale problems provide a powerful method for characterizing Markov processes. Stochastic control problems can also be formulated naturally as martingale problems (see for example Fleming (1983)), and our goal here is to exploit this formulation to give a general existence theorem for optimal solutions of a stochastic control problem in the finite time horizon and discounted cases (Sections 1,3), to construct the Nisio semigroup (Section 2), and to give conditions in terms of the generator of the Nisio semigroup under which the optimal solution can be approximated by solutions in which the control is piecewise constant (Sections 2,3). The proof of this last result involves showing that the value function of an appropriately defined discounted control problem is in the domain of the generator of the Nisio semigroup.

Research presented here was supported in part by the National Science Foundation contract DMS-8401360.

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Alfredo Germani

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© 1987 Springer-Verlag

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Kurtz, T.G. (1987). Martingale problems for controlled processes. In: Germani, A. (eds) Stochastic Modelling and Filtering. Lecture Notes in Control and Information Sciences, vol 91. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0009051

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  • DOI: https://doi.org/10.1007/BFb0009051

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-17575-9

  • Online ISBN: 978-3-540-47461-6

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