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作者机构:School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan 430074 China National Engineering Laboratory for Educational Big Data Central China Normal University Wuhan 430079 China Department of Electrical Engineering City University of Hong Kong Hong Kong SAR China
出 版 物:《Physical Review E》 (物理学评论E辑:统计、非线性和软体物理学)
年 卷 期:2022年第106卷第1期
页 面:014611-014611页
核心收录:
学科分类:07[理学] 070203[理学-原子与分子物理] 0702[理学-物理学]
基 金:State Grid Corporation of China, SGCC, (5100-202199557A-0-5-ZN) State Grid Corporation of China, SGCC
主 题:Collective behavior in networks Network phase transitions Pattern formation Self-organized systems
摘 要:Collective decision making in a biological motion group requires fast and robust transmission of information. Typically, directional switching information propagation across the whole group obeys a linear dispersion law. However, conventional dynamic collective motion models, such as the Vicsek model and the Couzin model did not take into account ultrafast directional synchronous motions. In the present paper, a multiparticle model is proposed based on inertial spin self-propel action, which can provide adequate description of such group motion. By considering both spin mechanism and collision avoidance, the proposed self-propelled particle spin model can nicely describe collective motion with fast directional switching. By analyzing the order parameter of the group-velocity synchronization, a mechanism of group decision making is revealed, which is based on the difference between two clusters of divergent leaders, showing a transition from the compromising phase (i.e., following the group average) to the preferred phase (i.e., aligning to a leader cluster). The finding provides new insight to the decision-making process of followers when they face with divergent leaders in group motion.