Inverse boundary problem for a mean field game system with probability density constraint
Analysis of PDEs
2024-02-22 v1 Optimization and Control
Abstract
By following the study in [24], we consider an inverse boundary problem for the mean field game system where a probability density constraint is enforced on the game agents. That is, we consider the case that reflective boundary conditions are enforced and hence the population distribution of the game agents should be treated as a probability measure which preserves both positivity and the total population. This poses significant challenges for the corresponding inverse problems in constructing suitable ``probing modes" which should fulfill such a probability density constraint. We develop an effective scheme in tackling such a case which is new to the literature.
Cite
@article{arxiv.2402.13274,
title = {Inverse boundary problem for a mean field game system with probability density constraint},
author = {Hongyu Liu and Shen Zhang},
journal= {arXiv preprint arXiv:2402.13274},
year = {2024}
}
Comments
arXiv admin note: substantial text overlap with arXiv:2212.09110