Infection-Based Norm Emergence in Multi-Agent Complex Networks

Authors:
Norman Salazar;Juan A. Rodriguez-Aguilar;Josep Ll. Arcos
Affiliations:
IIIA, Artificial Intelligence Research Institute, CSIC, Spanish National Research Council, Spain, email: norman@iiia.csic.es;IIIA, Artificial Intelligence Research Institute, CSIC, Spanish National Research Council, Spain, email: jar@iiia.csic.es;IIIA, Artificial Intelligence Research Institute, CSIC, Spanish National Research Council, Spain, email: arcos@iiia.csic.es
Venue:
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Year:
2008

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Abstract

We propose a computational model that facilitates agents in a MAS to collaboratively evolve their norms to reach the best norm conventions. Our approach borrows from the social contagion phenomenon to exploit the notion of positive infection: agents with good behaviors become infectious to spread their norms in the agent society. By combining infection and innovation, our computational model helps a MAS establish better norm conventions even when a sub-optimal one has fully settled in the population.