Mean field games of controls: Finite difference approximations
We consider a class of mean field games in which the agents interact through both their states and controls, and we focus on situations in which a generic agent tries to adjust her speed (control) to an average speed (the average is made in a neighborhood in the state space). In such cases, the mono...
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doaj-764b164aa71b48cda97d0425773046652021-03-11T01:19:37ZengAIMS PressMathematics in Engineering2640-35012021-03-013313510.3934/mine.2021024Mean field games of controls: Finite difference approximationsYves Achdou0Ziad Kobeissi1Université de Paris and Sorbonne Université, CNRS, Laboratoire Jacques-Louis Lions, (LJLL), F-75006 Paris, FranceUniversité de Paris and Sorbonne Université, CNRS, Laboratoire Jacques-Louis Lions, (LJLL), F-75006 Paris, FranceWe consider a class of mean field games in which the agents interact through both their states and controls, and we focus on situations in which a generic agent tries to adjust her speed (control) to an average speed (the average is made in a neighborhood in the state space). In such cases, the monotonicity assumptions that are frequently made in the theory of mean field games do not hold, and uniqueness cannot be expected in general. Such model lead to systems of forward-backward nonlinear nonlocal parabolic equations; the latter are supplemented with various kinds of boundary conditions, in particular Neumann-like boundary conditions stemming from reflection conditions on the underlying controled stochastic processes. The present work deals with numerical approximations of the above megntioned systems. After describing the finite difference scheme, we propose an iterative method for solving the systems of nonlinear equations that arise in the discrete setting; it combines a continuation method, Newton iterations and inner loops of a bigradient like solver. The numerical method is used for simulating two examples. We also make experiments on the behaviour of the iterative algorithm when the parameters of the model vary.http://www.aimspress.com/article/doi/10.3934/mine.2021024?viewType=HTMLmean field gamesinteractions via controlscrowd motionnumerical simulationsfinite difference method |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yves Achdou Ziad Kobeissi |
spellingShingle |
Yves Achdou Ziad Kobeissi Mean field games of controls: Finite difference approximations Mathematics in Engineering mean field games interactions via controls crowd motion numerical simulations finite difference method |
author_facet |
Yves Achdou Ziad Kobeissi |
author_sort |
Yves Achdou |
title |
Mean field games of controls: Finite difference approximations |
title_short |
Mean field games of controls: Finite difference approximations |
title_full |
Mean field games of controls: Finite difference approximations |
title_fullStr |
Mean field games of controls: Finite difference approximations |
title_full_unstemmed |
Mean field games of controls: Finite difference approximations |
title_sort |
mean field games of controls: finite difference approximations |
publisher |
AIMS Press |
series |
Mathematics in Engineering |
issn |
2640-3501 |
publishDate |
2021-03-01 |
description |
We consider a class of mean field games in which the agents interact through both their states and controls, and we focus on situations in which a generic agent tries to adjust her speed (control) to an average speed (the average is made in a neighborhood in the state space). In such cases, the monotonicity assumptions that are frequently made in the theory of mean field games do not hold, and uniqueness cannot be expected in general. Such model lead to systems of forward-backward nonlinear nonlocal parabolic equations; the latter are supplemented with various kinds of boundary conditions, in particular Neumann-like boundary conditions stemming from reflection conditions on the underlying controled stochastic processes. The present work deals with numerical approximations of the above megntioned systems. After describing the finite difference scheme, we propose an iterative method for solving the systems of nonlinear equations that arise in the discrete setting; it combines a continuation method, Newton iterations and inner loops of a bigradient like solver. The numerical method is used for simulating two examples. We also make experiments on the behaviour of the iterative algorithm when the parameters of the model vary. |
topic |
mean field games interactions via controls crowd motion numerical simulations finite difference method |
url |
http://www.aimspress.com/article/doi/10.3934/mine.2021024?viewType=HTML |
work_keys_str_mv |
AT yvesachdou meanfieldgamesofcontrolsfinitedifferenceapproximations AT ziadkobeissi meanfieldgamesofcontrolsfinitedifferenceapproximations |
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1724226128273473536 |