Consensus in networks of mobile communicating agents

TL;DR

This paper studies how groups of mobile, communicating agents reach consensus through local interactions, analyzing the effects of movement and communication range on convergence time and memory requirements.

Contribution

It introduces a general two-dimensional motion model combined with the minimal naming game to analyze consensus emergence in mobile agent networks, identifying key regimes and scaling behaviors.

Findings

Different regimes of convergence based on emission range and mobility.

Scaling laws for consensus time and memory usage.

Insights into cognitive requirements for agents in dynamic networks.

Abstract

Populations of mobile and communicating agents describe a vast array of technological and natural systems, ranging from sensor networks to animal groups. Here, we investigate how a group-level agreement may emerge in the continuously evolving network defined by the local interactions of the moving individuals. We adopt a general scheme of motion in two dimensions and we let the individuals interact through the minimal naming game, a prototypical scheme to investigate social consensus. We distinguish different regimes of convergence determined by the emission range of the agents and by their mobility, and we identify the corresponding scaling behaviors of the consensus time. In the same way, we rationalize also the behavior of the maximum memory used during the convergence process, which determines the minimum cognitive/storage capacity needed by the individuals. Overall, we believe that the simple and general model presented in this paper can represent a helpful reference for a better understanding of the behavior of populations of mobile agents.