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arXiv · 2402.09297

Reconstructing a state-independent cost function in a mean-field game model

Kui Ren·Nathan Soedjak·Kewei Wang·Hongyu Zhai
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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.

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Kui Ren, Nathan Soedjak, Kewei Wang, Hongyu Zhai. 2024-02-14. Reconstructing a state-independent cost function in a mean-field game model. https://arxiv.org/abs/2402.09297

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