Emergent clustering due to quorum sensing interactions in active matter

TL;DR

This study models how local sensing interactions among agents lead to emergent clustering behaviors, revealing that attraction can occur even in anti-social scenarios, with implications for designing collective robotic systems.

Contribution

Introduces a simple agent-based model demonstrating emergent clustering due to quorum sensing, highlighting attraction in both social and anti-social behaviors through simulations.

Findings

Positive correlations indicating attraction can emerge in anti-social behavior.

Emergent clustering occurs without explicit orientation information.

Model insights applicable to robotic swarm design.

Abstract

Many organisms in nature use local interactions to generate global cooperative phenomena. To unravel how the behavior of individuals generates effective interactions within a group, we introduce a simple model, wherein each agent senses the presence of others nearby and changes its physical motion accordingly. This generates non-physical, or virtual interactions between agents. We study the radial distribution function and the cluster size distribution to quantify the emergent interactions for both social and anti-social behavior; We identify social behavior as when an agent exhibits a tendency to remain in the vicinity of other agents, whereas anti-social behavior as when it displays a tendency to escape from the vicinity of others. Using Langevin dynamics simulations in two and three spatial dimensions, we discover that under certain conditions, positive correlations, which indicate attraction can emerge even in the case of anti-social behavior. Our results are potentially useful for designing robotic swimmers that can swim collectively only based on sensing the distance to their neighbors, without measuring any orientational information.