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

Biophysics and Physicobiology

Kazuki Horikawa¹  Udoy S. Basak²  Tamiki Komatsuzaki²  Md. Motaleb Hossain³  Sulimon Sattari³ 

[1] Department of Optical Imaging, The Institute of Biomedical Sciences, Tokushima University Graduate School, Tokushima 770-8503, Japan;Graduate School of Life Science, Transdisciplinary Life Science Course, Hokkaido University, Sapporo, Hokkaido 060-0812, Japan;Research Center of Mathematics for Social Creativity, Research Institute for Electronic Science, Hokkaido University, Sapporo, Hokkaido 001-0020, Japan;

关键词: causality;    transfer entropy;    leader-follower;    classification;    vicsek model;   

DOI  :  10.2142/biophysico.bppb-v18.015

来源: DOAJ

【 摘 要 】

Synchronized movement of (both unicellular and multicellular) systems can be observed almost everywhere. Understanding of how organisms are regulated to synchronized behavior is one of the challenging issues in the field of collective motion. It is hypothesized that one or a few agents in a group regulate(s) the dynamics of the whole collective, known as leader(s). The identification of the leader (influential) agent(s) is very crucial. This article reviews different mathematical models that represent different types of leadership. We focus on the improvement of the leader-follower classification problem. It was found using a simulation model that the use of interaction domain information significantly improves the leader-follower classification ability using both linear schemes and information-theoretic schemes for quantifying influence. This article also reviews different schemes that can be used to identify the interaction domain using the motion data of agents.

【 授权许可】

Unknown