On Symmetric Continuum Opinion Dynamics

This paper investigates the asymptotic behavior of some common opinion dynamic models in a continuum of agents. We show that as long as the interactions among the agents are symmetric, the distribution of the agents' opinion converges. We also investigate whether convergence occurs in a stronger sense than merely in distribution, namely, whether the opinion of almost every agent converges. We show that while this is not the case in general, it becomes true under plausible assumptions on inter-agent interactions, namely that agents with similar opinions exert a non-negligible pull on each other, or that the interactions are entirely determined by their opinions via a smooth function.

[1]  Jorge Cortes,et al.  Notes on averaging over acyclic digraphs and discrete coverage control , 2006, CDC.

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

[3]  John N. Tsitsiklis,et al.  Continuous-Time Average-Preserving Opinion Dynamics with Opinion-Dependent Communications , 2009, SIAM J. Control. Optim..

[4]  Stephen P. Boyd,et al.  A scheme for robust distributed sensor fusion based on average consensus , 2005, IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005..

[5]  Tamer Basar,et al.  Termination time of multidimensional Hegselmann-Krause opinion dynamics , 2013, 2013 American Control Conference.

[6]  Paolo Frasca,et al.  Continuous and discontinuous opinion dynamics with bounded confidence , 2012 .

[7]  Francesco Bullo,et al.  Opinion Dynamics in Heterogeneous Networks: Convergence Conjectures and Theorems , 2011, SIAM J. Control. Optim..

[8]  Patrick Billingsley,et al.  Probability and Measure. , 1986 .

[9]  Xiaoming Hu,et al.  Opinion consensus of modified Hegselmann-Krause models , 2012, CDC.

[10]  Reza Olfati-Saber,et al.  Consensus and Cooperation in Networked Multi-Agent Systems , 2007, Proceedings of the IEEE.

[11]  Mark Braverman,et al.  On the convergence of the Hegselmann-Krause system , 2012, ITCS '13.

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

[13]  Samuel Martin,et al.  Continuous-Time Consensus Under Non-Instantaneous Reciprocity , 2014, IEEE Transactions on Automatic Control.

[14]  Jan Lorenz,et al.  A stabilization theorem for dynamics of continuous opinions , 2005, 0708.2981.

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

[16]  F. Fagnani,et al.  Scaling limits for continuous opinion dynamics systems , 2009 .

[17]  Peter Hegarty,et al.  A Quadratic Lower Bound for the Convergence Rate in the One-Dimensional Hegselmann–Krause Bounded Confidence Dynamics , 2014, Discret. Comput. Geom..

[18]  Terrence Tao,et al.  An Introduction To Measure Theory , 2011 .

[19]  U. Krause A DISCRETE NONLINEAR AND NON–AUTONOMOUS MODEL OF CONSENSUS FORMATION , 2007 .

[20]  Asuman E. Ozdaglar,et al.  Distributed Subgradient Methods for Multi-Agent Optimization , 2009, IEEE Transactions on Automatic Control.

[21]  Bernard Chazelle,et al.  The Dynamics of Influence Systems , 2012, 2012 IEEE 53rd Annual Symposium on Foundations of Computer Science.

[22]  J. Shohat,et al.  The problem of moments , 1943 .

[23]  Francesco Bullo,et al.  Eulerian Opinion Dynamics with Bounded Confidence and Exogenous Inputs , 2012 .

[24]  John N. Tsitsiklis,et al.  On Krause's Multi-Agent Consensus Model With State-Dependent Connectivity , 2008, IEEE Transactions on Automatic Control.

[25]  Alexander Olshevsky,et al.  Efficient information aggregation strategies for distributed control and signal processing , 2010, 1009.6036.

[26]  L. Moreau,et al.  Stability of continuous-time distributed consensus algorithms , 2004, 2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601).

[27]  Richard M. Murray,et al.  Consensus problems in networks of agents with switching topology and time-delays , 2004, IEEE Transactions on Automatic Control.

[28]  Stephen P. Boyd,et al.  A space-time diffusion scheme for peer-to-peer least-squares estimation , 2006, 2006 5th International Conference on Information Processing in Sensor Networks.

[29]  Luc Moreau,et al.  Stability of multiagent systems with time-dependent communication links , 2005, IEEE Transactions on Automatic Control.

[30]  D. Pollard A User's Guide to Measure Theoretic Probability by David Pollard , 2001 .

[31]  John N. Tsitsiklis,et al.  Convergence of Type-Symmetric and Cut-Balanced Consensus Seeking Systems , 2011, IEEE Transactions on Automatic Control.

[32]  Pavel Yu. Chebotarev,et al.  Coordination in multiagent systems and Laplacian spectra of digraphs , 2009, ArXiv.

[33]  John N. Tsitsiklis,et al.  Parallel and distributed computation , 1989 .

[34]  Paolo Frasca,et al.  Existence and approximation of probability measure solutions to models of collective behaviors , 2010, Networks Heterog. Media.

[35]  KEITH CONRAD,et al.  DIFFERENTIATING UNDER THE INTEGRAL SIGN , 2011 .

[36]  Wei Ren,et al.  Information consensus in multivehicle cooperative control , 2007, IEEE Control Systems.

[37]  Han-Lim Choi,et al.  Consensus-Based Decentralized Auctions for Robust Task Allocation , 2009, IEEE Transactions on Robotics.

[38]  S. Dragomir Some Gronwall Type Inequalities and Applications , 2003 .

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