4 papers
Initialization-driven neural generation and training for high-dimensional optimal control and first-order mean field games
Mouhcine Assouli, Justina Gianatti, Badr Missaoui +1
This paper first introduces a method to approximate the value function of high-dimensional optimal control by neural networks. Based on the established relationship between Pontrya…
Approximation of deterministic mean field games under polynomial growth conditions on the data
Justina Gianatti, Francisco J. Silva, Ahmad Zorkot
We consider a deterministic mean field games problem in which a typical agent solves an optimal control problem where the dynamics is affine with respect to the control and the cos…
Approximation of deterministic mean field games with control-affine dynamics
Justina Gianatti, Francisco J. Silva
We consider deterministic mean field games where the dynamics of a typical agent is non-linear with respect to the state variable and affine with respect to the control variable. P…
A Lagrangian approach for aggregative mean field games of controls with mixed and final constraints
Joseph Frédéric Bonnans, Justina Gianatti, Laurent Pfeiffer
The objective of this paper is to analyze the existence of equilibria for a class of deterministic mean field games of controls. The interaction between players is due to both a co…