On the relaxed mean-field stochastic control problem

Khaled Bahlali, Meriem Mezerdi*, Brahim Mezerdi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

This paper is concerned with optimal control problems for systems governed by mean-field stochastic differential equation, in which the control enters both the drift and the diffusion coefficient. We prove that the relaxed state process, associated with measure valued controls, is governed by an orthogonal martingale measure rather than a Brownian motion. In particular, we show by a counter example that replacing the drift and diffusion coefficient by their relaxed counterparts does not define a true relaxed control problem. We establish the existence of an optimal relaxed control, which can be approximated by a sequence of strict controls. Moreover, under some convexity conditions, we show that the optimal control is realized by a strict control.

Original languageEnglish
Article number1850024
JournalStochastics and Dynamics
Volume18
Issue number3
DOIs
StatePublished - 1 Jun 2018
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2018 World Scientific Publishing Company.

Keywords

  • Mean-field stochastic differential equation
  • approximation
  • martingale measure
  • relaxed control
  • tightness
  • weak convergence

ASJC Scopus subject areas

  • Modeling and Simulation

Fingerprint

Dive into the research topics of 'On the relaxed mean-field stochastic control problem'. Together they form a unique fingerprint.

Cite this