Well-posedness and mean-field limit estimate of a consensus-based algorithm for multiplayer games
Optimization and Control
2025-05-21 v1 Classical Analysis and ODEs
Probability
Abstract
Recently, the paper [12] introduces a derivative-free consensus-based particle method that finds the Nash equilibrium of non-convex multiplayer games, where it proves the global exponential convergence in the sense of mean-field law. This paper aims to address theoretical gaps in [12], specifically by providing a quantitative estimate of the mean-field limit with respect to the number of particles, as well as establishing the well-posedness of both the finite particle model and the corresponding mean-field dynamics.
Cite
@article{arxiv.2505.13632,
title = {Well-posedness and mean-field limit estimate of a consensus-based algorithm for multiplayer games},
author = {Hui Huang and Jethro Warnett},
journal= {arXiv preprint arXiv:2505.13632},
year = {2025}
}