Agreement dynamics on small-world networks

TL;DR

This paper investigates how small-world network topology influences the dynamics of the Naming Game, revealing a crossover from local to global agreement behavior and effects on convergence speed and cognitive effort.

Contribution

It provides a detailed analysis of the Naming Game dynamics on small-world networks, highlighting the impact of network topology on convergence and memory requirements.

Findings

Existence of a crossover time scale proportional to N/p^2

Local topology induces coarsening dynamics reducing memory load

Small-world topology accelerates convergence in late stages

Abstract

In this paper we analyze the effect of a non-trivial topology on the dynamics of the so-called Naming Game, a recently introduced model which addresses the issue of how shared conventions emerge spontaneously in a population of agents. We consider in particular the small-world topology and study the convergence towards the global agreement as a function of the population size $N$ as well as of the parameter $p$ which sets the rate of rewiring leading to the small-world network. As long as $p \gg 1/N$ there exists a crossover time scaling as $N/p^2$ which separates an early one-dimensional-like dynamics from a late stage mean-field-like behavior. At the beginning of the process, the local quasi one-dimensional topology induces a coarsening dynamics which allows for a minimization of the cognitive effort (memory) required to the agents. In the late stages, on the other hand, the mean-field like topology leads to a speed up of the convergence process with respect to the one-dimensional case.