The Emergence of Complex Hierarchical Hub Social Network In The Mesa Verde Village Simulation Using Cultural Learning

Ziad Kobti, University of Windsor; Robert G. Reynolds, Wayne State University; Timothy A. Kohler, Washington State University

In this paper we extend the cultural framework previously developed for the Village multi-agent simulation in Swarm to include the emergence of a hub network from two base networks. The first base network is kinship, over which generalized reciprocal exchange is defined, and the second is the economic network where agents carry out balanced reciprocal exchange. Agents, or households, are able to procure several resources. We use Cultural Algorithms as a framework for the emergence of social intelligence at both individual and cultural levels. Successful agents on both networks can promote themselves to be included in the hub network where they can develop exchange links to other hubs. The collective effect of the hub network is representative of the quality of life in the population and serves as indicator for motives behind the mysterious emigration from the region. Knowledge represents the development and use of exchange relationships between agents. The presence of defectors on the hub network improved resilience of the social system while maintaining the population size as that observed where no defectors were present. This suggests a tendency for the social system to favor larger hub formations over less social individuals or those with weaker ties.


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