The Policy Iteration Algorithm for Average Continuous Control of Piecewise Deterministic Markov Processes

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dc.creatorCosta, O. L. V.
dc.creatorDufour, F.
dc.date2009-02-16
dc.date.accessioned2026-07-07T12:42:15Z
dc.date.available2026-07-07T12:42:15Z
dc.descriptionThe 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.
dc.identifierhttps://arxiv.org/abs/0902.2673
dc.identifierhttp://arxiv.org/abs/0902.2673
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/220011
dc.subjectProbability
dc.subject60J25, 90C40, 93E20
dc.titleThe Policy Iteration Algorithm for Average Continuous Control of Piecewise Deterministic Markov Processes
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