TY - JOUR
T1 - Particle approximation of one-dimensional Mean-Field-Games with local interactions
AU - Francesco, Marco Di
AU - Duisembay, Serikbolsyn
AU - Gomes, Diogo A.
AU - Ribeiro, Ricardo de Lima
N1 - KAUST Repository Item: Exported on 2022-04-27
Acknowledged KAUST grant number(s): OSR-CRG2021-4674
Acknowledgements: M. Di Francesco was supported by KAUST during his visit in 2020. S. Duisembay, D. A. Gomes and R. Ribeiro were partially supported by King Abdullah University of Science and Technology (KAUST) baseline funds and KAUST OSR-CRG2021-4674.
PY - 2022/3
Y1 - 2022/3
N2 - We study a particle approximation for one-dimensional first-order Mean-Field-Games (MFGs) with local interactions with planning conditions. Our problem comprises a system of a Hamilton-Jacobi equation coupled with a transport equation. As we deal with the planning problem, we prescribe initial and terminal distributions for the transport equation. The particle approximation builds on a semi-discrete variational problem. First, we address the existence and uniqueness of a solution to the semi-discrete variational problem. Next, we show that our discretization preserves some previously identified conserved quantities. Finally, we prove that the approximation by particle systems preserves displacement convexity. We use this last property to establish uniform estimates for the discrete problem. We illustrate our results for the discrete problem with numerical examples.
AB - We study a particle approximation for one-dimensional first-order Mean-Field-Games (MFGs) with local interactions with planning conditions. Our problem comprises a system of a Hamilton-Jacobi equation coupled with a transport equation. As we deal with the planning problem, we prescribe initial and terminal distributions for the transport equation. The particle approximation builds on a semi-discrete variational problem. First, we address the existence and uniqueness of a solution to the semi-discrete variational problem. Next, we show that our discretization preserves some previously identified conserved quantities. Finally, we prove that the approximation by particle systems preserves displacement convexity. We use this last property to establish uniform estimates for the discrete problem. We illustrate our results for the discrete problem with numerical examples.
UR - http://hdl.handle.net/10754/671167
UR - https://www.aimsciences.org/article/doi/10.3934/dcds.2022025
U2 - 10.3934/dcds.2022025
DO - 10.3934/dcds.2022025
M3 - Article
SN - 1078-0947
JO - Discrete & Continuous Dynamical Systems
JF - Discrete & Continuous Dynamical Systems
ER -