Bounded Confidence Model with Fixed Uncertainties and Extremists: The Opinions Can Keep Fluctuating Indefinitely
Author(s) -
JeanDenis Mathias,
Sylvie Huet,
Guillaume Deffuant
Publication year - 2016
Publication title -
journal of artificial societies and social simulation
Language(s) - English
Resource type - Journals
ISSN - 1460-7425
DOI - 10.18564/jasss.2967
Subject(s) - attractor , bounded function , statistical physics , state (computer science) , cluster analysis , stationary state , stationary solution , bounded rationality , mathematics , physics , computer science , mathematical analysis , statistics , algorithm , artificial intelligence , quantum mechanics
The bounded confidence model and its variants applied to moderate and extremist agents exhibit three types of attractors: central clusters, double extreme and single extreme clusters. These attractors are observed when the models include a dynamics on the uncertainties tending to decrease the moderate uncertainties when interacting with extremists. We show here that a new stationary state appears when the uncertainties are fixed, for large uncertainties of the moderates. In this stationary state, the opinions of moderate agents keep fluctuating without clustering, altogether forming a stable density which shape changes significantly when the parameters vary.
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