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Article Dans Une Revue Methodology and Computing in Applied Probability Année : 2022

Numerical resolution of McKean-Vlasov FBSDEs using neural networks *

Résumé

We propose several algorithms to solve McKean-Vlasov Forward Backward Stochastic Differential Equations (FBSDEs). Our schemes rely on the approximating power of neural networks to estimate the solution or its gradient through minimization problems. As a consequence, we obtain methods able to tackle both mean-field games and mean-field control problems in moderate dimension. We analyze the numerical behavior of our algorithms on several examples including non linear quadratic models.
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Dates et versions

hal-03326051 , version 1 (25-08-2021)
hal-03326051 , version 2 (05-03-2022)

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Maximilien Germain, Joseph Mikael, Xavier Warin. Numerical resolution of McKean-Vlasov FBSDEs using neural networks *. Methodology and Computing in Applied Probability, In press. ⟨hal-03326051v2⟩
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