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Impulsive Control for Continuous-Time Markov Decision Processes

Part of:Markov processes

Published online by Cambridge University Press:  04 January 2016

François Dufour and
Alexei B. Piunovskiy
François Dufour*
Affiliation:
Université Bordeaux, IMB and INRIA Bordeaux Sud-Ouest
Alexei B. Piunovskiy*
Affiliation:
University of Liverpool
*
∗ Postal address: INRIA Bordeaux Sud-Ouest, 200 Avenue de la Vieille Tour, 33405 Talence cedex, France. Email address: dufour@math.u-bordeaux1.fr
∗∗ Postal address: Department of Mathematical Sciences, University of Liverpool, Liverpool, L69 7ZL, UK. Email address: piunov@liverpool.ac.uk
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Abstract

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In this paper our objective is to study continuous-time Markov decision processes on a general Borel state space with both impulsive and continuous controls for the infinite time horizon discounted cost. The continuous-time controlled process is shown to be nonexplosive under appropriate hypotheses. The so-called Bellman equation associated to this control problem is studied. Sufficient conditions ensuring the existence and the uniqueness of a bounded measurable solution to this optimality equation are provided. Moreover, it is shown that the value function of the optimization problem under consideration satisfies this optimality equation. Sufficient conditions are also presented to ensure on the one hand the existence of an optimal control strategy, and on the other hand the existence of a ε-optimal control strategy. The decomposition of the state space into two disjoint subsets is exhibited where, roughly speaking, one should apply a gradual action or an impulsive action correspondingly to obtain an optimal or ε-optimal strategy. An interesting consequence of our previous results is as follows: the set of strategies that allow interventions at time t = 0 and only immediately after natural jumps is a sufficient set for the control problem under consideration.

Keywords

Impulsive controlcontinuous controlcontinuous-time Markov decision processdiscounted cost

MSC classification

Primary:90C40: Markov and semi-Markov decision processes
Secondary:60J25: Continuous-time Markov processes on general state spaces

Information

Type
General Applied Probability
Information
Advances in Applied Probability , Volume 47 , Issue 1 , March 2015, pp. 106 - 127
Copyright
© Applied Probability Trust 

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