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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…

Probability · Mathematics 2013-05-28 Adrien Brandejsky , Benoîte de Saporta , François Dufour

We present a numerical method to compute the survival function and the moments of the exit time for a piecewise-deterministic Markov process (PDMP). Our approach is based on the quantization of an underlying discrete-time Markov chain…

Probability · Mathematics 2011-08-31 Adrien Brandejsky , Benoîte de Saporta , François Dufour

This paper presents a numerical method to calculate the value function for a general discounted impulse control problem for piecewise deterministic Markov processes. Our approach is based on a quantization technique for the underlying…

Probability · Mathematics 2011-08-31 Benoîte de Saporta , François Dufour

Designing efficient and rigorous numerical methods for sequential decision-making under uncertainty is a difficult problem that arises in many applications frameworks. In this paper we focus on the numerical solution of a subclass of…

Statistics Theory · Mathematics 2025-11-07 Alice Cleynen , Benoîte de Saporta

This paper is dedicated to the investigation of a new numerical method to approximate the optimal stopping problem for a discrete-time continuous state space Markov chain under partial observations. It is based on a two-step discretization…

Optimization and Control · Mathematics 2016-02-16 Benoîte de Saporta , François Dufour , Christophe Nivot

We consider a change-point detection problem for a simple class of Piecewise Deterministic Markov Processes (PDMPs). A continuous-time PDMP is observed in discrete time and through noise, and the aim is to propose a numerical method to…

Optimization and Control · Mathematics 2017-09-28 Alice Cleynen , Benoîte de Saporta

This paper investigates the random horizon optimal stopping problem for measure-valued piecewise deterministic Markov processes (PDMPs). This is motivated by population dynamics applications, when one wants to monitor some characteristics…

Probability · Mathematics 2018-09-14 Bertrand Cloez , Benoîte de Saporta , Maud Joubaud

This paper deals with the long run average continuous control problem of piecewise deterministic Markov processes (PDMP's) taking values in a general Borel space and with compact action space depending on the state variable. The control…

Probability · Mathematics 2008-09-03 O. L. V. Costa , F. Dufour

Piecewise deterministic Markov processes (PDMPs) are a class of stochastic processes with applications in several fields of applied mathematics spanning from mathematical modeling of physical phenomena to computational methods. A PDMP is…

Probability · Mathematics 2022-09-30 Andrea Bertazzi , Joris Bierkens , Paul Dobson

We present a numerical method to compute expectations of functionals of a piecewise-deterministic Markov process. We discuss time dependent functionals as well as deterministic time horizon problems. Our approach is based on the…

Probability · Mathematics 2012-01-31 Adrien Brandejsky , Benoîte de Saporta , François Dufour

Piecewise deterministic Markov processes (PDMPs) are a class of continuous-time Markov processes that were recently used to develop a new class of Markov chain Monte Carlo algorithms. However, the implementation of the processes is…

Computation · Statistics 2024-08-08 Charly Andral , Kengo Kamatani

The main goal of this paper is to derive sufficient conditions for the existence of an optimal control strategy for the long run average continuous control problem of piecewise deterministic Markov processes (PDMP's) taking values in a…

Probability · Mathematics 2008-12-05 O. L. V. Costa , F. Dufour

In this paper, we are interested in the exact simulation of a class of Piecewise Deterministic Markov Processes (PDMP). We show how to perform efficient thinning algorithms depending on the jump rate bound. For different types of jump rate…

Probability · Mathematics 2022-02-10 Vincent Lemaire , Michèle Thieullen , Nicolas Thomas

This paper deals with the general discounted impulse control problem of a piecewise deterministic Markov process. We investigate a new family of epsilon-optimal strategies. The construction of such strategies is explicit and only…

Probability · Mathematics 2016-03-28 Benoîte de Saporta , François Dufour , Alizée Geeraert

We give a short overview of recent results on a specific class of Markov process: the Piecewise Deterministic Markov Processes (PDMPs). We first recall the definition of these processes and give some general results. On more specific cases…

Statistics Theory · Mathematics 2013-09-25 Romain Azaïs , Jean-Baptiste Bardet , Alexandre Genadot , Nathalie Krell , Pierre-André Zitt

In this paper we consider a control problem for a Partially Observable Piecewise Deterministic Markov Process of the following type: After the jump of the process the controller receives a noisy signal about the state and the aim is to…

Optimization and Control · Mathematics 2021-07-21 Nicole Bäuerle , Dirk Lange

Hybrid systems, and Piecewise Deterministic Markov Processes in particular, are widely used to model and numerically study systems exhibiting multiple time scales in biochemical reaction kinetics and related areas. In this paper an almost…

Numerical Analysis · Mathematics 2011-12-07 Martin G. Riedler

This paper attempts to study the optimal stopping time for semi-Markov processes (SMPs) under the discount optimization criteria with unbounded cost rates. In our work, we introduce an explicit construction of the equivalent semi-Markov…

Probability · Mathematics 2021-01-05 Fang Chen , Xianping Guo , Zhong-Wei Liao

This papers deals with the constrained discounted control of piecewise deterministic Markov process (PDMPs) in general Borel spaces. The control variable acts on the jump rate and transition measure, and the goal is to minimize the total…

Optimization and Control · Mathematics 2014-02-26 Oswaldo Costa , François Dufour

Piecewise-deterministic Markov processes (PDMPs) offer a powerful stochastic modeling framework that combines deterministic trajectories with random perturbations at random times. Estimating their local characteristics (particularly the…

Methodology · Statistics 2025-12-29 Romain Azaïs , Solune Denis
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