Literature DB >> 30070518

Anatomy of leadership in collective behaviour.

Joshua Garland1, Andrew M Berdahl1, Jie Sun2, Erik M Bollt2.   

Abstract

Understanding the mechanics behind the coordinated movement of mobile animal groups (collective motion) provides key insights into their biology and ecology, while also yielding algorithms for bio-inspired technologies and autonomous systems. It is becoming increasingly clear that many mobile animal groups are composed of heterogeneous individuals with differential levels and types of influence over group behaviors. The ability to infer this differential influence, or leadership, is critical to understanding group functioning in these collective animal systems. Due to the broad interpretation of leadership, many different measures and mathematical tools are used to describe and infer "leadership," e.g., position, causality, influence, and information flow. But a key question remains: which, if any, of these concepts actually describes leadership? We argue that instead of asserting a single definition or notion of leadership, the complex interaction rules and dynamics typical of a group imply that leadership itself is not merely a binary classification (leader or follower), but rather, a complex combination of many different components. In this paper, we develop an anatomy of leadership, identify several principal components, and provide a general mathematical framework for discussing leadership. With the intricacies of this taxonomy in mind, we present a set of leadership-oriented toy models that should be used as a proving ground for leadership inference methods going forward. We believe this multifaceted approach to leadership will enable a broader understanding of leadership and its inference from data in mobile animal groups and beyond.

Year:  2018        PMID: 30070518     DOI: 10.1063/1.5024395

Source DB:  PubMed          Journal:  Chaos        ISSN: 1054-1500            Impact factor:   3.642


  5 in total

1.  Naïve individuals promote collective exploration in homing pigeons.

Authors:  Gabriele Valentini; Theodore P Pavlic; Sara Imari Walker; Stephen C Pratt; Dora Biro; Takao Sasaki
Journal:  Elife       Date:  2021-12-20       Impact factor: 8.140

2.  Modes of information flow in collective cohesion.

Authors:  Sulimon Sattari; Udoy S Basak; Ryan G James; Louis W Perrin; James P Crutchfield; Tamiki Komatsuzaki
Journal:  Sci Adv       Date:  2022-02-09       Impact factor: 14.136

3.  Disentangling influence over group speed and direction reveals multiple patterns of influence in moving meerkat groups.

Authors:  Baptiste Averly; Vivek H Sridhar; Vlad Demartsev; Gabriella Gall; Marta Manser; Ariana Strandburg-Peshkin
Journal:  Sci Rep       Date:  2022-08-16       Impact factor: 4.996

4.  Transfer entropy dependent on distance among agents in quantifying leader-follower relationships.

Authors:  Udoy S Basak; Sulimon Sattari; Motaleb Hossain; Kazuki Horikawa; Tamiki Komatsuzaki
Journal:  Biophys Physicobiol       Date:  2021-05-15

5.  Decoding collective communications using information theory tools.

Authors:  K R Pilkiewicz; B H Lemasson; M A Rowland; A Hein; J Sun; A Berdahl; M L Mayo; J Moehlis; M Porfiri; E Fernández-Juricic; S Garnier; E M Bollt; J M Carlson; M R Tarampi; K L Macuga; L Rossi; C-C Shen
Journal:  J R Soc Interface       Date:  2020-03-18       Impact factor: 4.118

  5 in total

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