This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Binary and Multivariate Stochastic Models of Consensus Formation
November/December 2005 (vol. 7 no. 6)
pp. 67-73
Raul Toral, IMEDEA
Konstantin Klemm, Leipzig University
The emergence of consensus is a current paradigm in many computer simulation studies of social sciences problems. The specific issue is how to determine when the dynamics of a set of interacting agents that can choose among several options (political vote, opinion, cultural features, and so on) lead to a consensus in one of those options, or when a state with several coexisting social options prevails. Many researchers seek to identify the mechanisms that produce the latter, called a polarized state, in the face of general convergent dynamics. The problem of spatially distributed agents, for example, shares many characteristics with the problem of domain growth in phase-transition kinetics: consensus emerges when a single spatial domain grows to occupy the entire system, whereas polarization corresponds to a situation in which the system isn?t ordered and different spatial domains compete. In this article, we consider stochastic dynamic models studied via computer simulation.
Index Terms:
stochastic modeling, voter models, dynamic models
Citation:
Maxi San Miguel, Victor M. Egu?luz, Raul Toral, Konstantin Klemm, "Binary and Multivariate Stochastic Models of Consensus Formation," Computing in Science and Engineering, vol. 7, no. 6, pp. 67-73, Nov.-Dec. 2005, doi:10.1109/MCSE.2005.114
Usage of this product signifies your acceptance of the Terms of Use.