Special Issue on FLAIRS 2005: Knowledge Acquisition and Representation; Guest Editors: I. Russell, Z. Markov and L. B. HolderNo Access

THE EMERGENCE OF SOCIAL NETWORK HIERARCHY USING CULTURAL ALGORITHMS

ZIAD KOBTI

School of Computer Science, University of Windsor, 401 Sunset Avenue, Windsor, Ontario N9B-3P4, Canada

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ROBERT G. REYNOLDS

Department of Computer Science, Wayne State University, 5143 Cass Avenue, Detroit, Michigan 49202, USA

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, and

TIM A. KOHLER

Department of Anthropology, Washington State University, PO Box 644910, College 150, Pullman, Washington 99164-4910, USA

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https://doi.org/10.1142/S0218213006003065Cited by:12 (Source: Crossref)

Abstract

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 in 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 an 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 in the hub network improved resilience of the social system while maintaining the population size at that observed where no defectors were present.

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