Small world dynamics and the process of knowledge diffusion: The case of the metropolitan area of Greater Santiago de Chile

This paper aims to understand some of the mechanisms which dominate the phenomenon of knowledge diffusion in the process that is called 'interactive learning'. We examine how knowledge spreads in a network in which agents have 'face-to-face' learning interactions. We define a social network structured as a graph consisting of agents (vertices) and connections (edges) and situated on a grid which resembles the geographical characteristics of the metropolitan area of Greater Santiago de Chile. The target of this simulation is to test whether knowledge diffuses homogeneously or whether it follows some biased path generating geographical divergence between a core area and a periphery. We also investigate the efficiency of our 'preference' model of agent decision-making and show that this system evolves towards a small-world type network.