Interacting Discovery Processes on Complex Networks.

Enrico Ubaldi,Vito Latora,Iacopo Iacopini,Vittorio Loreto,Gabriele Di Bona

doi:10.1103/physrevlett.125.248301

Abstract

Innovation is the driving force of human progress. Recent urn models reproduce well the dynamics through which the discovery of a novelty may trigger further ones, in an expanding space of opportunities, but neglect the effects of social interactions. Here we focus on the mechanisms of collective exploration, and we propose a model in which many urns, representing different explorers, are coupled through the links of a social network and exploit opportunities coming from their contacts. We study different network structures showing, both analytically and numerically, that the pace of discovery of an explorer depends on its centrality in the social network. Our model sheds light on the role that social structures play in discovery processes.

Highlights

Innovation is the driving force of human progress
We focus on the mechanisms of collective exploration, and we propose a model in which many urns, representing different explorers, are coupled through the links of a social network and exploit opportunities coming from their contacts
Urns can be used to model discovery processes, if opportunely combined with the concept of the adjacent possible (AP)—the set of all those things which are one step away from what is already known (Kauffman [36]). This formulation of the AP, which dates back to concepts previously introduced by Farmer, Langton, and others [37,38,39], has been translated into the urn model with triggering (UMT), a particular process in which the space expands together with the discovery dynamics, and the appearance of a novelty opens up the possibilities of further discoveries [4,40,41,42,43]

Summary

Introduction

Innovation is the driving force of human progress. Recent urn models reproduce well the dynamics through which the discovery of a novelty may trigger further ones, in an expanding space of opportunities, but neglect the effects of social interactions. We study different network structures showing, both analytically and numerically, that the pace of discovery of an explorer depends on its centrality in the social network.

Results

Conclusion