Consensus Convergence with Stochastic Effects

We consider a stochastic, continuous state and time opinion model where each agent’s opinion locally interacts with other agents’ opinions in the system, and there is also exogenous randomness. The interaction tends to create clusters of common opinion. By using linear stability analysis of the associated nonlinear Fokker–Planck equation that governs the empirical density of opinions in the limit of infinitely many agents, we can estimate the number of clusters, the time to cluster formation, and the critical strength of randomness so as to have cluster formation. We also discuss the cluster dynamics after their formation, the width and the effective diffusivity of the clusters. Finally, the long-term behavior of clusters is explored numerically. Extensive numerical simulations confirm our analytical findings.

[1]  Sébastien Motsch,et al.  Heterophilious Dynamics Enhances Consensus , 2013, SIAM Rev..

[2]  L. Schimansky-Geier,et al.  Networks of noisy oscillators with correlated degree and frequency dispersion , 2012, 1208.6491.

[3]  Rainer Hegselmann,et al.  Opinion dynamics under the influence of radical groups, charismatic leaders, and other constant signals: A simple unifying model , 2015, Networks Heterog. Media.

[4]  Emilio Hernández-García,et al.  The noisy Hegselmann-Krause model for opinion dynamics , 2013, 1309.2858.

[5]  Jonathan H. Manton,et al.  Opinion dynamics with noisy information , 2013, 52nd IEEE Conference on Decision and Control.

[6]  Dirk Helbing,et al.  Individualization as Driving Force of Clustering Phenomena in Humans , 2010, PLoS Comput. Biol..

[7]  Jan Lorenz,et al.  Continuous Opinion Dynamics under Bounded Confidence: A Survey , 2007, 0707.1762.

[8]  Francesco Bullo,et al.  Eulerian Opinion Dynamics with Bounded Confidence and Exogenous Inputs , 2012, SIAM J. Appl. Dyn. Syst..

[9]  Xiaoming Hu,et al.  Opinion consensus of modified Hegselmann-Krause models , 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).

[10]  P. Markowich,et al.  Boltzmann and Fokker–Planck equations modelling opinion formation in the presence of strong leaders , 2009, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[11]  Giacomo Como,et al.  Scaling limits for continuous opinion dynamics systems , 2009, 2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

[12]  E. Tadmor,et al.  From particle to kinetic and hydrodynamic descriptions of flocking , 2008, 0806.2182.

[13]  Adrian Carro,et al.  The Role of Noise and Initial Conditions in the Asymptotic Solution of a Bounded Confidence, Continuous-Opinion Model , 2012, Journal of Statistical Physics.

[14]  J. Boudec,et al.  The Bounded Confidence Model Of Opinion Dynamics , 2010, 1006.3798.

[15]  R. Toral,et al.  Diffusing opinions in bounded confidence processes , 2010, 1004.1102.

[16]  J.N. Tsitsiklis,et al.  Convergence in Multiagent Coordination, Consensus, and Flocking , 2005, Proceedings of the 44th IEEE Conference on Decision and Control.

[17]  John N. Tsitsiklis,et al.  On the 2R conjecture for multi-agent systems , 2007, 2007 European Control Conference (ECC).

[18]  T. Kurtz,et al.  Particle representations for a class of nonlinear SPDEs , 1999 .

[19]  Guillaume Deffuant,et al.  Mixing beliefs among interacting agents , 2000, Adv. Complex Syst..

[20]  François Baccelli,et al.  Stochastic bounded confidence opinion dynamics , 2014, 53rd IEEE Conference on Decision and Control.

[21]  Rainer Hegselmann,et al.  Opinion dynamics and bounded confidence: models, analysis and simulation , 2002, J. Artif. Soc. Soc. Simul..

[22]  Nicolas Lanchier,et al.  Stochastic Dynamics on Hypergraphs and the Spatial Majority Rule Model , 2013, 1301.0151.

[23]  Pierre-Emmanuel Jabin,et al.  Clustering and asymptotic behavior in opinion formation , 2014 .

[24]  Raul Toral,et al.  Noisy continuous-opinion dynamics , 2009, 0906.0441.

[25]  J. Gärtner On the McKean‐Vlasov Limit for Interacting Diffusions , 1988 .

[26]  Claudio Canuto,et al.  An Eulerian Approach to the Analysis of Krause's Consensus Models , 2012, SIAM J. Control. Optim..

[27]  D. Dawson Critical dynamics and fluctuations for a mean-field model of cooperative behavior , 1983 .