Using the tools of the Markov decision processes, we justify the dynamic programming approach to the optimal impulse control of deterministic dynamical systems. We prove the equivalence of the integral and differential forms of the optimality equation. The theory is illustrated by an example from mathematical epidemiology. The developed methods can be also useful for the study of piecewise deterministic Markov processes
This research concerns the development of new optimal control methodologies and applications. In the...
© 2020, Pleiades Publishing, Ltd. We consider continuous and impulse control of a Markov chain (MC) ...
On s’intéresse au problème de contrôle impulsionnel à horizon infini avec facteur d’oubli pour les p...
When solving optimal impulse control problems, one can use the dynamic programming approach in two d...
This paper concerns the optimal impulse control of piecewise deterministic Markov processes (PDPs). ...
This paper deals with the general discounted impulse control problem of a piecewisedeterministic Mar...
This paper considers an optimal impulse control problem of dynamical systems generated by a flow. Th...
International audiencePiecewise deterministic Markov processes (PDMPs) have been introduced by M.H.A...
In this paper, we study the infinite-horizon expected discounted continuous-time optimal control pro...
In this paper, we consider the gradual-impulse control problem of continuous-time Markov decision pr...
AbstractWe consider a gradual-impulse control problem of continuous-time Markov decision processes, ...
We are interested in a discounted impulse control problem with infinite horizon forpiecewise determi...
We consider the optimal impulse control of a dynamical system defined by a fixed uncontrolled flow. ...
Abstract. A piecewise deterministic Markov process (PDP) is a continuous time Markov pro-cess consis...
Stochastic control refers to the optimal control of systems subject to randomness. Impulse and singu...
This research concerns the development of new optimal control methodologies and applications. In the...
© 2020, Pleiades Publishing, Ltd. We consider continuous and impulse control of a Markov chain (MC) ...
On s’intéresse au problème de contrôle impulsionnel à horizon infini avec facteur d’oubli pour les p...
When solving optimal impulse control problems, one can use the dynamic programming approach in two d...
This paper concerns the optimal impulse control of piecewise deterministic Markov processes (PDPs). ...
This paper deals with the general discounted impulse control problem of a piecewisedeterministic Mar...
This paper considers an optimal impulse control problem of dynamical systems generated by a flow. Th...
International audiencePiecewise deterministic Markov processes (PDMPs) have been introduced by M.H.A...
In this paper, we study the infinite-horizon expected discounted continuous-time optimal control pro...
In this paper, we consider the gradual-impulse control problem of continuous-time Markov decision pr...
AbstractWe consider a gradual-impulse control problem of continuous-time Markov decision processes, ...
We are interested in a discounted impulse control problem with infinite horizon forpiecewise determi...
We consider the optimal impulse control of a dynamical system defined by a fixed uncontrolled flow. ...
Abstract. A piecewise deterministic Markov process (PDP) is a continuous time Markov pro-cess consis...
Stochastic control refers to the optimal control of systems subject to randomness. Impulse and singu...
This research concerns the development of new optimal control methodologies and applications. In the...
© 2020, Pleiades Publishing, Ltd. We consider continuous and impulse control of a Markov chain (MC) ...
On s’intéresse au problème de contrôle impulsionnel à horizon infini avec facteur d’oubli pour les p...