An interacting particle system modelling aggregation behavior : from individuals to populations

In this paper we investigate the stochastic modelling of a spatially structured biological population subject to social interaction. The biological motivation comes from the analysis of field experiments on a species of ants which exhibits a clear tendency to aggregate, still avoiding overcrowding. The model we propose here provides an explanation of this experimental behavior in terms of long-ranged aggregation and short-ranged repulsion mechanisms among individuals, in addition to an individual random dispersal described by a Brownian motion. Further, based on a law of large numbers, we discuss the convergence, for large N, of a system of stochastic differential equations describing the evolution of N individuals (Lagrangian approach) to a deterministic integro-differential equation describing the evolution of the mean-field spatial density of the population (Eulerian approach).