Abstract
In this paper the results of several agent-based simulations, aiming to test the effectiveness of norm recognition and the role of normative beliefs in norm emergence are presented and discussed. Rather than mere behavioral regularities, norms are here seen as behaviors spreading to the extent that and because the corresponding commands and beliefs do spread as well. More specifically, we will present simulations aimed to compare the behavior of a population of normative agents provided with a norm recognition module and a population of social conformers whose behavior is determined only by a rule of imitation. The results of these simulations show that under specific conditions, i.e. moving from one social setting to another, imitators are not able to converge in a stable way on one single behavior; vice-versa, normative agents (equipped with the norm recognition module) are able to converge on one single behavior.
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At the moment, the normative beliefs’ salience can only increase, depending on how many instances of the same normative belief are stored in the Normative Board. This feature has the negative effect that some norms become highly salient, exerting an excessive interference with the decisional process of the agent. We are now improving the model, adding the possibility that, if the normative belief is inactive for a certain amount of time, its salience will decrease.
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Acknowledgments
This work was supported by the EMIL project (IST-033841), funded by the Future and Emerging Technologies program of the European Commission, in the framework of the initiative Simulating Emergent Properties in Complex Systems.
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Andrighetto, G., Campennì, M., Cecconi, F., Conte, R. (2010). The Complex Loop of Norm Emergence: A Simulation Model. In: Takadama, K., Cioffi-Revilla, C., Deffuant, G. (eds) Simulating Interacting Agents and Social Phenomena. Agent-Based Social Systems, vol 7. Springer, Tokyo. https://doi.org/10.1007/978-4-431-99781-8_2
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DOI: https://doi.org/10.1007/978-4-431-99781-8_2
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