Agent based models and opinion dynamics as markov chains
AbstractThis paper introduces a Markov chain approach that allows a rigorous analysis of agent based opinion dynamics as well as other related agent based models (ABM). By viewing the ABM dynamics as a micro description of the process, we show how the corresponding macro description is obtained by a projection construction. Then, well known conditions for lumpability make it possible to establish the cases where the macro model is stillMarkov. In this case we obtain a complete picture of the dynamics including the transient stage, the most interesting phase in applications. For such a purpose a crucial role is played by the type of probability distribution used to implement the stochastic part of the model which defines the updating rule and governs the dynamics. In addition, we show how restrictions in communication leading to the co–existence of different opinions follow from the emergence of new absorbing states. We describe our analysis in detail with some specific models of opinion dynamics. Generalizations concerning different opinion representations as well as opinion models with other interaction mechanisms are also discussed. We find that our method may be an attractive alternative to mean–field approaches and that this approach provides new perspectives on the modeling of opinion exchange dynamics, and more generally of other ABM.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by ISEG - School of Economics and Management, Department of Economics, University of Lisbon in its series Working Papers Department of Economics with number 2012/10.
Date of creation: Mar 2012
Date of revision:
Contact details of provider:
Postal: Department of Economics, ISEG - School of Economics and Management, University of Lisbon, Rua do Quelhas 6, 1200-781 LISBON, PORTUGAL
Web page: https://aquila1.iseg.ulisboa.pt/aquila/departamentos/EC
Agent Based Models; Opinion Dynamics; Markov chains; MicroMacro; Lumpability; Transient Dynamics.;
This paper has been announced in the following NEP Reports:
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- F. Slanina & H. Lavicka, 2003. "Analytical results for the Sznajd model of opinion formation," The European Physical Journal B - Condensed Matter and Complex Systems, Springer, vol. 35(2), pages 279-288, September.
- Joshua M. Epstein & Robert L. Axtell, 1996. "Growing Artificial Societies: Social Science from the Bottom Up," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262550253, December.
- Schelling, Thomas C, 1969. "Models of Segregation," American Economic Review, American Economic Association, vol. 59(2), pages 488-93, May.
- Luis R. Izquierdo & Segismundo S. Izquierdo & JosÃ© Manuel GalÃ¡n & Jos� Ignacio Santos, 2009. "Techniques to Understand Computer Simulations: Markov Chain Analysis," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(1), pages 6.
- F. Schweitzer & L. Behera, 2009. "Nonlinear voter models: the transition from invasion to coexistence," The European Physical Journal B - Condensed Matter and Complex Systems, Springer, vol. 67(3), pages 301-318, February.
- Grazzini, Jakob & Richiardi, Matteo, 2013.
"Consistent Estimation of Agent-Based Models by Simulated Minimum Distance,"
Department of Economics and Statistics Cognetti de Martiis. Working Papers
201335, University of Turin.
- Jakob Grazzini & Matteo G. Richiardi, 2013. "Consistent Estimation of Agent-Based Models by Simulated Minimum Distance," LABORatorio R. Revelli Working Papers Series 130, LABORatorio R. Revelli, Centre for Employment Studies.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Vitor Escaria).
If references are entirely missing, you can add them using this form.