Diffusion and growth in an evolving network

G.C.M.A. Ehrhardt, M. Marsili, F. Vega-Redondo
International Journal of Game Theory 34(3), 383, 2006.

We study a simple model of a population of agents whose interaction network co-evolves with knowledge diffusion and accumulation. Diffusion takes place along the current network and, reciprocally, network formation depends on the knowledge profile. Diffusion makes neighboring agents tend to display similar knowledge levels. On the other hand, similarity in knowledge favors network formation. The cumulative nonlinear effects induced by this interplay produce sharp transitions, equilibrium co-existence, and hysteresis, which sheds some light on why multiplicity of outcomes and segmentation in performance may persist resiliently over time in knowledge-based processes.

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