Work

Mean-field neural networks-based algorithms for McKean-Vlasov control problems *

Year: 2022

Type: preprint

Abstract: This paper is devoted to the numerical resolution of McKean-Vlasov control problems via the class of mean-field neural networks introduced in our companion paper [25] in order to learn the solution on the Wasserstein space. We propose several algorithms either based on dynamic programming with control learning by policy or value iteration, or backward SDE from stochastic maximum principle with global or local loss functions. Extensive numerical results on different examples are presented to illustrate the accuracy of each of our eight algorithms. We discuss and compare the pros and cons of all the tested methods.

Source: RePEc: Research Papers in Economics

DOI: 10.48550/arxiv.2212.11518

Authors: Pham, Huyên, Warin, Xavier

Institutions: Laboratoire de Probabilités, Statistique et Modélisation, Laboratoire de Finance des Marchés de l'Énergie

Language: English

Topic: Stochastic processes and financial applications

Subfield: Finance

Field: Economics, Econometrics and Finance

Domain: Social Sciences

Open Access status: green

OpenAlex ID: W4312121950

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Related to: 10