Imitation Combined with a Characteristic Stimulus Duration Results in Robust Collective Decision-Making
Abstract
For group-living animals, reaching consensus to stay cohesive is crucial for their fitness, particularly when collective motion starts and stops. Understanding the decision-making at individual and collective levels upon sudden disturbances is central in the study of collective animal behavior, and concerns the broader question of how information is distributed and evaluated in groups. Despite the relevance of the problem, well-controlled experimental studies that quantify the collective response of groups facing disruptive events are lacking. Here we study the behavior of groups of uninformed individuals subject to the departure and stop of a trained conspecific within small-sized groups. We find that the groups reach an effective consensus: either all uninformed individuals follow the trained one (and collective motion occurs) or none does it. Combining experiments and a simple mathematical model we show that the observed phenomena results from the interplay between simple mimetic rules and the characteristic duration of the stimulus, here, the time the trained individual is moving away. The proposed mechanism strongly depends on group size, as observed in the experiments, and though group splitting can occur, the most likely outcome is always a coherent collective group response (consensus). The prevalence of a consensus is expected even if the groups of naives face conflicting information, e.g. if groups contain two subgroups of trained individuals, one trained to stay and one trained to leave. Our results indicate that collective decision-making and consensus in (small) animal groups are likely to be self-organized phenomena that do not involve concertation or even communication among the group members.
- Publication:
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PLoS ONE
- Pub Date:
- October 2015
- DOI:
- 10.1371/journal.pone.0140188
- arXiv:
- arXiv:1512.07307
- Bibcode:
- 2015PLoSO..1040188T
- Keywords:
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- Physics - Biological Physics;
- Quantitative Biology - Populations and Evolution
- E-Print:
- PLoS ONE 10(10): e0140188 (2015)