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....

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Hauptverfasser: Morale, Daniela (VerfasserIn) , Capasso, Vincenzo (VerfasserIn) , Oelschläger, Karl (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: 2005
In: Journal of mathematical biology
Year: 2004, Jahrgang: 50, Heft: 1, Pages: 49-66
ISSN:1432-1416
DOI:10.1007/s00285-004-0279-1
Online-Zugang:Verlag, Volltext: http://dx.doi.org/10.1007/s00285-004-0279-1
Verlag, Volltext: https://link.springer.com/article/10.1007/s00285-004-0279-1
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Verfasserangaben:Daniela Morale, Vincenzo Capasso, Karl Oelschläger
Beschreibung
Zusammenfassung: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).
Beschreibung:First online: 05 July 2004
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Beschreibung:Online Resource
ISSN:1432-1416
DOI:10.1007/s00285-004-0279-1