Discrete Dynamics in Nature and Society
Volume 6 (2001), Issue 1, Pages 49-56
Complexity and state-transitions in social dependence networks
1Division of AI, Cognitive and Interaction Modelling, Institute of Psychology, Italian National Research Council (CNR), Roma V.le Marx 15–00137, Italy
2Division CEN/1, DCPT, Italian National Institute for Statistics (ISTAT), Roma Via Ravà 150–00142, Italy
Received 6 June 2000
Copyright © 2001 Giuliano Pistolesi and Pierluigi Modesti. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Computation of complexity in Social Dependence Networks is an interesting research domain to understand evolution processes and group exchange dynamics in natural and artificial intelligent Multi-Agent Systems. We perform an agent-based simulation by
NET-PLEX (Conte and Pistolesi, 2000), a new software system able both to build interdependence networks tipically emerging in Multi-Agent System scenarios and to investigate complexity phenomena, i.e., unstability and state-transitions like Hopf bifurcation (Nowak and Lewenstein, 1994), and to describe social self organization phenomena emerging in these artificial social systems by means of complexity measures similar to those introduced by Hubermann and Hogg (1986). By performing analysis of complexity in these kind of artificial societies we observed interesting phenomena in emerging organizations that suggest state-transitions induced by critical configurations of parameters describing the social system similar to those observed in many studies on state-transitions in bifurcation chaos (Schuster, 1988; Ruelle, 1989).