Mean field interaction on random graphs with dynamically changing multi-color edges

Erhan Bayraktar and Ruoyu Wu

Stochastic Processes and their Applications, 2021, vol. 141, issue C, 197-244

Abstract: We consider weakly interacting jump processes on time-varying random graphs with dynamically changing multi-color edges. The system consists of a large number of nodes in which the node dynamics depends on the joint empirical distribution of all the other nodes and the edges connected to it, while the edge dynamics depends only on the corresponding nodes it connects. Asymptotic results, including law of large numbers, propagation of chaos, and central limit theorems, are established. In contrast to the classic McKean–Vlasov limit, the limiting system exhibits a path-dependent feature in that the evolution of a given particle depends on its own conditional distribution given its past trajectory. We also analyze the asymptotic behavior of the system when the edge dynamics is accelerated. A law of large number and a propagation of chaos result is established, and the limiting system is given as independent McKean–Vlasov processes. Error between the two limiting systems, with and without acceleration in edge dynamics, is also analyzed.

Keywords: Dynamical random graphs; Mean field interaction; Propagation of chaos; Central limit theorems; Endogenous common noise; Exchangeability (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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DOI: 10.1016/j.spa.2021.07.005

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