TY - JOUR
T1 - Evolutionary Dynamics of Collective Behavior Selection and Drift
T2 - Flocking, Collapse, and Oscillation
AU - Tan, Shaolin
AU - Wang, Yaonan
AU - Chen, Yao
AU - Wang, Zhen
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2017/7
Y1 - 2017/7
N2 - 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.
AB - 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.
KW - Behavior networks
KW - behavior patterns
KW - evolutionary dynamics
KW - game theory
KW - stable equilibrium point
UR - http://www.scopus.com/inward/record.url?scp=84974794961&partnerID=8YFLogxK
U2 - 10.1109/TCYB.2016.2555316
DO - 10.1109/TCYB.2016.2555316
M3 - 文章
C2 - 27323386
AN - SCOPUS:84974794961
SN - 2168-2267
VL - 47
SP - 1694
EP - 1705
JO - IEEE Transactions on Cybernetics
JF - IEEE Transactions on Cybernetics
IS - 7
M1 - 7491286
ER -