The Policy Iteration Algorithm for Average Continuous Control of Piecewise Deterministic Markov Processes
Probability
2009-02-17 v1
Abstract
The main goal of this paper is to apply the so-called policy iteration algorithm (PIA) for 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. In order to do that we first derive some important properties for a pseudo-Poisson equation associated to the problem. In the sequence it is shown that the convergence of the PIA to a solution satisfying the optimality equation holds under some classical hypotheses and that this optimal solution yields to an optimal control strategy for the average control problem for the continuous-time PDMP in a feedback form.
Cite
@article{arxiv.0902.2673,
title = {The Policy Iteration Algorithm for Average Continuous Control of Piecewise Deterministic Markov Processes},
author = {O. L. V. Costa and F. Dufour},
journal= {arXiv preprint arXiv:0902.2673},
year = {2009}
}