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Hamilton-Jacobi-Bellman inequality for the average control of piecewise deterministic Markov processes
Abstract:ABSTRACT

The main goal of this paper is to study the infinite-horizon long run average continuous-time optimal control problem of piecewise deterministic Markov processes (PDMPs) with the control acting continuously on the jump intensity λ and on the transition measure Q of the process. We provide conditions for the existence of a solution to an integro-differential optimality inequality, the so called Hamilton-Jacobi-Bellman (HJB) equation, and for the existence of a deterministic stationary optimal policy. These results are obtained by using the so-called vanishing discount approach, under some continuity and compactness assumptions on the parameters of the problem, as well as some non-explosive conditions for the process.
Keywords:Average control  continuous control  Hamilton-Jacobi-Bellman inequality  piecewise deterministic Markov process  continuous-time Markov decision process
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