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DOI: 10.14569/IJACSA.2016.070769
PDF

Conditions Facilitating the Aversion of Unpopular Norms: An Agent-Based Simulation Study

Author 1: Zoofishan Zareen
Author 2: Muzna Zafar
Author 3: Kashif Zia

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 7, 2016.

  • Abstract and Keywords
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Abstract: People mostly facilitate and manage their social lives adhering to the prevalent norms. There are some norms which are unpopular, yet people adhere to them. Ironically, people at individual level do not agree to these norms, but, they still follow and even facilitate them. Irrespective of the social and psychological reasons behind their persistence, sometimes, for societal good, it is necessary to oppose and possibly avert the unpopular norms. In this paper, we model theorydriven computational specifications of Emperor’s Dilemma into an agent-based simulation, to understand the the conditions that result in emergence of unpopular norms. The reciprocal nature of persistence and aversion of norms, thus, is utilized to define situations under which these norms can be changed and averted. Simulation is performed under many interesting “what-if” questions. The simulation results reveal that under high density conditions of agent population with a high percentage of norm aversion activists, the aversion of unpopular norms can be achieved.

Keywords: Agent-based Modeling and Simulation; Emperor’s Dilemma; Complex Adaptive Systems.

Zoofishan Zareen, Muzna Zafar and Kashif Zia, “Conditions Facilitating the Aversion of Unpopular Norms: An Agent-Based Simulation Study” International Journal of Advanced Computer Science and Applications(IJACSA), 7(7), 2016. http://dx.doi.org/10.14569/IJACSA.2016.070769

@article{Zareen2016,
title = {Conditions Facilitating the Aversion of Unpopular Norms: An Agent-Based Simulation Study},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.070769},
url = {http://dx.doi.org/10.14569/IJACSA.2016.070769},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {7},
author = {Zoofishan Zareen and Muzna Zafar and Kashif Zia}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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