Growing artificial societies: social science from the bottom up
Growing artificial societies: social science from the bottom up
Sharing information across community portals with FOAFRealm
International Journal of Web Based Communities
Towards social-therapeutic robots: how to strategically implement a robot for social group therapy?
CIRA'09 Proceedings of the 8th IEEE international conference on Computational intelligence in robotics and automation
D-FOAF: distributed identity management with access rights delegation
ASWC'06 Proceedings of the First Asian conference on The Semantic Web
Envisioning complexity in healthcare systems through social networks
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
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Much work in complexity theory employs agent-based models in simulations of systems of multiple agents. Agent interaction follows some standard types of network topologies. My aim is to assess how recent advances in the statistical modeling of social networks may contribute to agent-based modeling traditions, specifically, by providing structural characterizations of a variety of network topologies. I illustrate the points by reference to a computational model for the evolution of cooperation among agents embedded in neighborhoods and by reference to complex, real social networks defined by the ties of political support between US Senators as revealed through ties of cosponsorship of legislation.