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集体行为中的领导力剖析。

Anatomy of leadership in collective behaviour.

作者信息

Garland Joshua, Berdahl Andrew M, Sun Jie, Bollt Erik M

机构信息

Santa Fe Institute, Santa Fe, New Mexico 87501, USA.

Department of Mathematics, Clarkson University, Potsdam, New York 13699, USA.

出版信息

Chaos. 2018 Jul;28(7):075308. doi: 10.1063/1.5024395.

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.

摘要

了解移动动物群体协同运动(集体运动)背后的机制,不仅能为它们的生物学和生态学提供关键见解,还能为受生物启发的技术和自主系统提供算法。越来越明显的是,许多移动动物群体由异质个体组成,这些个体对群体行为的影响程度和类型各不相同。推断这种差异影响(即领导力)的能力对于理解这些集体动物系统中的群体功能至关重要。由于对领导力的宽泛解释,人们使用了许多不同的测量方法和数学工具来描述和推断“领导力”,例如位置、因果关系、影响力和信息流。但一个关键问题仍然存在:这些概念中究竟哪一个(如果有的话)真正描述了领导力?我们认为,与其断言领导力的单一定义或概念,群体典型的复杂交互规则和动态意味着领导力本身不仅仅是二元分类(领导者或追随者),而是许多不同组成部分的复杂组合。在本文中,我们构建了领导力剖析,识别了几个主要组成部分,并提供了一个用于讨论领导力的通用数学框架。考虑到这种分类法的复杂性,我们提出了一组面向领导力的简化模型,这些模型应作为未来领导力推断方法的试验场。我们相信,这种对领导力的多方面方法将使人们更广泛地理解领导力及其从移动动物群体及其他群体的数据中进行的推断。

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