Hostname: page-component-78c5997874-4rdpn Total loading time: 0 Render date: 2024-11-18T18:20:16.913Z Has data issue: false hasContentIssue false
  • English
  • Français

Extending the Hegselmann–Krause Model III: From Single Beliefs to Complex Belief States

Published online by Cambridge University Press:  03 January 2012

Alexander Riegler  and
Igor Douven
Get access Rights & Permissions [Opens in a new window]

Abstract

In recent years, various computational models have been developed for studying the dynamics of belief formation in a population of epistemically interacting agents that try to determine the numerical value of a given parameter. Whereas in those models, agents’ belief states consist of single numerical beliefs, the present paper describes a model that equips agents with richer belief states containing many beliefs that, moreover, are logically interconnected. Correspondingly, the truth the agents are after is a theory (a set of sentences of a given language) rather than a numerical value. The agents epistemically interact with each other and also receive evidence in varying degrees of informativeness about the truth. We use computer simulations to study how fast and accurately such populations as wholes are able to approach the truth under differing combinations of settings of the key parameters of the model, such as the degree of informativeness of the evidence and the weight the agents give to the evidence.

Type
Research Article
Information
Episteme , Volume 6 , Issue 2 , June 2009 , pp. 145 - 163
Copyright
Copyright © Cambridge University Press 2009

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Deffuant, G., Neau, D., Amblard, F., and Weisbuch, G.. 2000. “Mixing Beliefs among Interacting Agents.” Advances in Complex Systems 3: 87–98.CrossRefGoogle Scholar
Dittmer, J. C. 2001. “Consensus Formation under Bounded Confidence.” Nonlinear Analysis 7: 4615–21.CrossRefGoogle Scholar
Douven, I. 2009. “Simulating Peer Disagreements.” Manuscript.Google Scholar
Douven, I. and Riegler, A.. 2009. “Extending the Hegselmann-Krause Model I.” Logic Journal of the IGPL, in press.CrossRefGoogle Scholar
Fortunato, S. 2005. “On the Consensus Threshold for the Opinion Dynamics of Krause-Hegselmann.” International Journal of Modern Physics C 16: 259–70.CrossRefGoogle Scholar
Gaylord, R. J. and D'Andria, L. J.. 1998. Simulating Society. New York: Springer.CrossRefGoogle Scholar
Hegselmann, R. and Krause, U.. 2002. “Opinion Dynamics and Bounded Confidence: Models, Analysis, and Simulations.” Journal of Artificial Societies and Social Simulation 5. http://jasss.soc.surrey.ac.uk/5/3/2.htmlGoogle Scholar
Hegselmann, R. and Krause, U.. 2005. “Opinion Dynamics Driven by Various Ways of Averaging.” Computational Economics 25: 381–405.CrossRefGoogle Scholar
Hegselmann, R. and Krause, U.. 2006. “Truth and Cognitive Division of Labor: First Steps towards a Computer Aided Social Epistemology.” Journal of Artificial Societies and Social Simulation 9. http://jasss.soc.surrey.ac.uk/9/3/10.htmlGoogle Scholar
Jacobmeier, D. 2004. “Multidimensional Consensus Model on a Barabási-Albert Network.” International Journal of Modern Physics C 16: 633–46.CrossRefGoogle Scholar
Kuipers, T. A. F. 2000. From Instrumentalism to Constructive Realism. Dordrecht: Kluwer.CrossRefGoogle Scholar
Lorenz, J. 2003. Mehrdimensionale Meinungsdynamik bei wechselndem Vertrauen. Diploma thesis, University of Bremen. http://nbn-resolving.de/urn:nbn:de:gbv:46-dipl000000564Google Scholar
Lorenz, J. 2007. “Continuous Opinion Dynamics under Bounded Confidence: A Survey.” International Journal of Modern Physics C 18: 1819–38.CrossRefGoogle Scholar
Lorenz, J. 2008. “Fostering Consensus in Multidimensional Continuous Opinion Dynamics under Bounded Confidence.” In Helbing, D. (ed.), Managing Complexity, pp. 321–34. Berlin: Springer.Google Scholar
Pluchino, A., Latora, V., and Rapisarda, A.. 2006. “Compromise and Synchronization in Opinion Dynamics.” European Physical Journal B 50: 169–76.CrossRefGoogle Scholar
Ramirez-Cano, D. and Pitt, J.. 2006. “Follow the Leader: Profiling Agents in an Opinion Formation Model of Dynamic Confidence and Individual Mind-Sets.” Proceedings of the 2006 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, pp. 660–7.Google Scholar
Riegler, A. and Douven, I.. 2009. “Extending the Hegselmann–Krause Model II.” In Kijania-Placek, K. (ed.), Proceedings of ECAP6. London: College Publications, in press.Google Scholar
Weisbuch, G., Deffuant, G., Amblard, F., and Nadal, J. P.. 2002. “Meet, Discuss and Segregate!” Complexity 7: 55–63.CrossRefGoogle Scholar