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Group performance is maximized by hierarchical competence distribution

Author

Listed:
  • Anna Zafeiris

    (Eötvös University)

  • Tamás Vicsek

    (Eötvös University
    Statistical and Biological Physics Research Group of HAS)

Abstract

Groups of people or even robots often face problems they need to solve together. Examples include collectively searching for resources, choosing when and where to invest time and effort, and many more. Although a hierarchical ordering of the relevance of the group members’ inputs during collective decision making is abundant, a quantitative demonstration of its origin and advantages using a generic approach has not been described yet. Here we introduce a family of models based on the most general features of group decision making, and show that the optimal distribution of competences is a highly skewed function with a structured fat tail. Our results are obtained by optimizing the groups’ compositions through identifying the best-performing distributions for both the competences and for the members’ flexibilities/pliancies. Potential applications include choosing the best composition for a group intended to solve a given task.

Suggested Citation

  • Anna Zafeiris & Tamás Vicsek, 2013. "Group performance is maximized by hierarchical competence distribution," Nature Communications, Nature, vol. 4(1), pages 1-8, December.
    • Handle: RePEc:nat:natcom:v:4:y:2013:i:1:d:10.1038_ncomms3484
    DOI: 10.1038/ncomms3484
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    Cited by:

    1. Hu, Fei & Zhao, Shangmei & Bing, Tao & Chang, Yiming, 2017. "Hierarchy in industrial structure: The cases of China and the USA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 871-882.
    2. Richard P Mann, 2021. "Evolution of heterogeneous perceptual limits and indifference in competitive foraging," PLOS Computational Biology, Public Library of Science, vol. 17(2), pages 1-20, February.
    3. Zafeiris, Anna & Koman, Zsombor & Mones, Enys & Vicsek, Tamás, 2017. "Phenomenological theory of collective decision-making," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 287-298.

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