title: Self-organized sorting limits behavioral variability in swarms.
abstract: Swarming is a phenomenon where collective motion arises from simple local interactions between typically identical individuals. Here, we investigate the effects of variability in behavior among the agents in finite swarms with both alignment and cohesive interactions. We show that swarming is abolished above a critical fraction of non-aligners who do not participate in alignment. In certain regimes, however, swarms above the critical threshold can dynamically reorganize and sort out excess non-aligners to maintain the average fraction close to the critical value. This persists even in swarms with a distribution of alignment interactions, suggesting a simple, robust and efficient mechanism that allows heterogeneously mixed populations to naturally regulate their composition and remain in a collective swarming state or even differentiate among behavioral phenotypes. We show that, for evolving swarms, this self-organized sorting behavior can couple to the evolutionary dynamics leading to new evolutionarily stable equilibrium populations set by the physical swarm parameters.
authors.affiliation: University of California Merced, Merced CA, USA.
authors.forename: Katherine
authors.initials: K
authors.lastname: Copenhagen
authors.affiliation: Stanford University, Stanford CA, USA.|Carnegie Institute of Washington, Stanford CA, USA.
authors.forename: David A
authors.initials: DA
authors.lastname: Quint
authors.affiliation: University of California Merced, Merced CA, USA.
authors.forename: Ajay
authors.initials: A
authors.lastname: Gopinathan
mesh_terms: D000465:Algorithms; D025041:Animal Migration / Q000502:physiology*; D000818:Animals; D003198:Computer Simulation; D008954:Models, Biological; D011157:Population Dynamics; D012919:Social Behavior; D013037:Spatial Behavior / Q000502:physiology*