Optimal stopping for partially observed piecewise-deterministic Markov processes

Abstract : This paper deals with the optimal stopping problem under partial observation for piecewise-deterministic Markov processes. We first obtain a recursive formulation of the optimal filter process and derive the dynamic programming equation of the partially observed optimal stopping problem. Then, we propose a numerical method, based on the quantization of the discrete-time filter process and the inter-jump times, to approximate the value function and to compute an actual $\epsilon$-optimal stopping time. We prove the convergence of the algorithms and bound the rates of convergence.
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Contributor : Benoîte De Saporta <>
Submitted on : Tuesday, November 20, 2012 - 2:12:26 PM
Last modification on : Wednesday, December 5, 2018 - 9:02:07 AM

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Adrien Brandejsky, Benoîte De Saporta, François Dufour. Optimal stopping for partially observed piecewise-deterministic Markov processes. Stochastic Processes and their Applications, Elsevier, 2013, 123, pp.3201-3238. 〈10.1016/j.spa.2013.03.006〉. 〈hal-00755052〉

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