Reconstructing a state-independent cost function in a mean-field game model
Analysis of PDEs
2024-08-16 v2 Optimization and Control
Abstract
In this short note, we consider an inverse problem to a mean-field games system where we are interested in reconstructing the state-independent running cost function from observed value-function data. We provide an elementary proof of a uniqueness result for the inverse problem using the standard multilinearization technique. One of the main features of our work is that we insist that the population distribution be a probability measure, a requirement that is not enforced in some of the existing literature on theoretical inverse mean-field games.
Keywords
Cite
@article{arxiv.2402.09297,
title = {Reconstructing a state-independent cost function in a mean-field game model},
author = {Kui Ren and Nathan Soedjak and Kewei Wang and Hongyu Zhai},
journal= {arXiv preprint arXiv:2402.09297},
year = {2024}
}