Evolutionary Dynamics of Collective Behavior Selection and Drift: Flocking, Collapse, and Oscillation

Shaolin Tan, Yaonan Wang, Yao Chen, Zhen Wang

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23 引用 (Scopus)

摘要

Behavioral choice is ubiquitous across a wide range of interactive decision-making processes and a myriad of scientific disciplines. With regard to this issue, one entitative problem is actually to understand how collective social behaviors form and evolve among populations when they face a variety of conflict alternatives. In this paper, a selection-drift dynamic model is formulated to characterize the behavior imitation and exploration processes in social populations. Based on the proposed framework, several typical behavior evolution patterns, including behavioral flocking, collapse, and oscillation, are reproduced with different kinds of behavior networks. Interestingly, for the selection-drift dynamics on homogeneous symmetric behavior networks, we unveil the phase transition from behavioral flocking to collapse and derive the bifurcation diagram of the evolutionary stable behaviors in social behavior evolution. While via analyzing the survival conditions of the best behavior on heterogeneous symmetric behavior networks, we propose a selection-drift mechanism to guarantee consensus at the optimal behavior. Moreover, when the selection-drift dynamics on asymmetric behavior networks is simulated, it is shown that breaking the symmetry in behavior networks can induce various behavioral oscillations. These obtained results may shed new insights into understanding, detecting, and further controlling how social norm and cultural trends evolve.

源语言英语
文章编号7491286
页(从-至)1694-1705
页数12
期刊IEEE Transactions on Cybernetics
47
7
DOI
出版状态已出版 - 7月 2017

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