USING a model inspired by networks of coupled neurons, researchers from the University of Sheffield, led by Andreagiovanni Reina, have investigated the process by which swarms of honeybees choose the best nesting location among a set of potential sites with different qualities.
The study shows that the frequency of signalling among bees is a key to their decision-making. If signalling is too scarce it hampers the attainment of consensus within the swarm; if it is too frequent it causes the bees to commit to early-discovered options that are of inferior quality. The authors suggest that ecological factors determining the density of suitable nest sites may have led to selective pressures on the evolution of an optimal signalling frequency. The work was published in the latest issue of Physical Review E.
According to the authors, to date the nest-site selection process has mostly been modelled and theoretically analysed for the case of binary decisions. However, when the number of alternative nests is larger than two, the decision process dynamics qualitatively change. Whereas, they say, previous binary models highlighted the crucial role of inhibitory stop-signalling, the key parameter in our new analysis is the relative time invested by swarm members in individual discovery and in signalling behaviours.
They point to similar decision-making problems manifest in diverse other situations, from societies of microbes to committees of medical experts. They suggest that the simplicity of the adaptive decision-making characteristics of their model for house hunting swarm of honeybees could also be used in the design of decentralised decision-making systems, particularly in collective robotics and in cognitive radio networks.
Compiled by R. Ramachandran
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