Knowledge diffusion dynamics and network properties of face-to-face interactions

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 interact by word of mouth. The social network is structured as a network graph consisting of agents (vertices) and connections (edges) and is situated on a wrapped cellular automata grid forming a torus. The target of this simulation is to test whether knowledge diffuses in a homogeneous way or whether it follows some biased path towards convergence or divergence.