Title: | Noise improves collective decision-making by ants in dynamic environments |
Author(s): | Dussutour A; Beekman M; Nicolis SC; Meyer B; |
Address: | "School of Biological Sciences and Centre for Mathematical Biology, The University of Sydney, New South Wales 2006, Australia. dussutour@cict.fr" |
ISSN/ISBN: | 1471-2954 (Electronic) 0962-8452 (Print) 0962-8452 (Linking) |
Abstract: | "Recruitment via pheromone trails by ants is arguably one of the best-studied examples of self-organization in animal societies. Yet it is still unclear if and how trail recruitment allows a colony to adapt to changes in its foraging environment. We study foraging decisions by colonies of the ant Pheidole megacephala under dynamic conditions. Our experiments show that P. megacephala, unlike many other mass recruiting species, can make a collective decision for the better of two food sources even when the environment changes dynamically. We developed a stochastic differential equation model that explains our data qualitatively and quantitatively. Analysing this model reveals that both deterministic and stochastic effects (noise) work together to allow colonies to efficiently track changes in the environment. Our study thus suggests that a certain level of noise is not a disturbance in self-organized decision-making but rather serves an important functional role" |
Keywords: | "Animals Ants/*physiology Appetitive Behavior/physiology Decision Making/*physiology *Models, Theoretical *Social Behavior *Stochastic Processes;" |
Notes: | "MedlineDussutour, A Beekman, M Nicolis, S C Meyer, B eng Research Support, Non-U.S. Gov't England 2009/09/25 Proc Biol Sci. 2009 Dec 22; 276(1677):4353-61. doi: 10.1098/rspb.2009.1235. Epub 2009 Sep 23" |