Title

Using The Process Of Norm Emergence To Model Consensus Formation

Keywords

Agent-Based Model; Complex Systems; Computational Social Science; Consensus; Emergence; Norms; Self-Organization; Simulation

Abstract

Every agent in a society initially possesses a set of personal norms. Group norms emerge when agents interact with one another and exchange information in such a way that multiple agents begin to acquire the same personal norm. This emergence is the result of information transmission, social enforcement, and internalization. If a population contains a single group norm, as a result of every agent in the population acquiring the same personal norm, then it can be said that a consensus has been reached by the population. We model the formation of consensus in silico by adapting a recently developed model of norm emergence to a multi-agent simulation. A screening experiment is conducted to identify the significant parameters of our model and verify that our model is capable of producing a consensus. The experimental results show that our model can attain consensus as well as two additional states of information equilibrium. The results also indicate that both network structure and agent behavior play an important role in the formation of consensus. In addition, it is shown that the formation of consensus is sensitive to the simulation parameter settings, and certain values can prevent its formation entirely. © 2011 IEEE.

Publication Date

11-21-2011

Publication Title

Proceedings - 2011 5th IEEE International Conference on Self-Adaptive and Self-Organizing Systems, SASO 2011

Number of Pages

148-157

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/SASO.2011.26

Socpus ID

81255147983 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/81255147983

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