Mean-Field Limit of Non-exchangeable Multi-agent Systems Over Hypergraphs with Unbounded Rank

Abstract

Interacting particle systems are known for their ability to generate large-scale self-organized structures from simple local interaction rules between each agent and its neighbors. In addition to studying their emergent behavior, a main focus of the mathematical community has been concentrated on deriving their large-population limit. In particular, the mean-field limit consists of describing the limit system by its population density in the product space of positions and labels. The strategy to derive such limits is often based on a careful combination of methods ranging from analysis of PDEs and stochastic analysis, to kinetic equations and graph theory. In this article, we focus on a generalization of multi-agent systems that includes higher-order interactions, which has largely captured the attention of the applied community in the last years. In such models, interactions between individuals are no longer assumed to be binary (i.e., between a pair of particles). Instead, individuals are allowed to interact by groups so that a full group jointly generates a nonlinear force on any given individual. The underlying graph of connections is then replaced by a hypergraph, which we assume to be dense, but possibly nonuniform and of unbounded rank. For the first time in the literature, we show that when the interaction kernels are regular enough, then the mean-field limit is determined by a limiting Vlasov-type equation, where the hypergraph limit is encoded by a so-called UR-hypergraphon (unbounded-rank hypergraphon), and where the resulting mean-field force admits infinitely-many orders of interactions.

The authors' abstract, as published at the source. Journal of Nonlinear Science, 2026 · DOI ↗