Modes of information flow in collective cohesion

被引:9
|
作者
Sattari, Sulimon [1 ]
Basak, Udoy S. [1 ,2 ]
James, Ryan G. [3 ,4 ]
Perrin, Louis W. [1 ,5 ]
Crutchfield, James P. [4 ]
Komatsuzaki, Tamiki [1 ,6 ,7 ]
机构
[1] Hokkaido Univ, Res Inst Elect Sci, Res Ctr Math Social Creat, Kita Ku, Kita 20,Nishi 10, Sapporo, Hokkaido 0010020, Japan
[2] Pabna Univ Sci & Technol, Pabna 6600, Bangladesh
[3] Reddit Inc, 420 Taylor St, San Francisco, CA 94102 USA
[4] Univ Calif Davis, Complex Sci Ctr, Dept Phys, Davis, CA 95616 USA
[5] Ecole Normale Super Rennes, Robert Schumann Campus,Av Ker Lann, F-35170 Bruz, France
[6] Hokkaido Univ, Inst Chem React Design & Discovery WPI ICReDD, Kita Ku, Kita 21 Nishi 10, Sapporo, Hokkaido 0010021, Japan
[7] Hokkaido Univ, Grad Sch Chem Sci & Engn, Mat Chem & Energy Course, Kita Ku, Kita 13,Nishi 8, Sapporo, Hokkaido 0600812, Japan
关键词
KEY AGREEMENT; DRIVEN;
D O I
10.1126/sciadv.abj1720
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Pairwise interactions are fundamental drivers of collective behavior-responsible for group cohesion. The abiding question is how each individual influences the collective. However, time-delayed mutual information and transfer entropy, commonly used to quantify mutual influence in aggregated individuals, can result in misleading interpretations. Here, we show that these information measures have substantial pitfalls in measuring information flow between agents from their trajectories. We decompose the information measures into three distinct modes of information flow to expose the role of individual and group memory in collective behavior. It is found that decomposed information modes between a single pair of agents reveal the nature of mutual influence involving many-body nonadditive interactions without conditioning on additional agents. The pairwise decomposed modes of information flow facilitate an improved diagnosis of mutual influence in collectives.
引用
收藏
页数:13
相关论文
共 50 条
  • [1] Cohesion, order and information flow in the collective motion of mixed-species shoals
    Ward, Ashley J. W.
    Schaerf, T. M.
    Burns, A. L. J.
    Lizier, J. T.
    Crosato, E.
    Prokopenko, M.
    Webster, M. M.
    ROYAL SOCIETY OPEN SCIENCE, 2018, 5 (12):
  • [2] Modalities, Cohesion, and Information Flow
    Kavvos, G. A.
    PROCEEDINGS OF THE ACM ON PROGRAMMING LANGUAGES-PACMPL, 2019, 3 (POPL):
  • [3] Both information and social cohesion determine collective decisions in animal groups
    Miller, Noam
    Garnier, Simon
    Hartnett, Andrew T.
    Couzin, Iain D.
    PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2013, 110 (13) : 5263 - 5268
  • [4] Information flow and influence in collective choice
    Stasser, Garold
    Abele, Susanne
    Parsons, Sandra Vaughan
    GROUP PROCESSES & INTERGROUP RELATIONS, 2012, 15 (05) : 619 - 635
  • [5] COLLECTIVE COHESION FORCES IN POLYMERS
    HUYSKENS, P
    VANDEVYVERE, P
    COLEMONTSVANDEVYVERE, C
    BULLETIN DES SOCIETES CHIMIQUES BELGES, 1991, 100 (01): : 49 - 52
  • [6] Hydrodynamics of Fermi arcs: Bulk flow and surface collective modes
    Gorbar, E. V.
    Miransky, V. A.
    Shovkovy, I. A.
    Sukhachov, P. O.
    PHYSICAL REVIEW B, 2019, 99 (15)
  • [7] Information Flow in a Boolean Network Model of Collective Behavior
    Porfiri, Maurizio
    IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS, 2018, 5 (04): : 1864 - 1874
  • [8] Inference of Causal Information Flow in Collective Animal Behavior
    Lord W.M.
    Sun J.
    Ouellette N.T.
    Bollt E.M.
    IEEE Trans. Mol. Biol. Multi-Scale Commun., 1 (107-116): : 107 - 116
  • [9] MODES OF COHESION IN CONTEMPORARY ENGLISH POETRY
    TROTTER, D
    LANGUAGE AND STYLE, 1980, 13 (02): : 109 - 119
  • [10] Collective Modes in a Quantum
    Gazit, Snir
    Podolsky, Daniel
    Nonne, Heloise
    Auerbach, Assa
    Arovas, Daniel P.
    PHYSICAL REVIEW LETTERS, 2016, 117 (08)