Self-Assembling of Networks in an Agent-Based Model

TL;DR

This paper introduces a model where simple Brownian agents autonomously form stable, network-like structures between nodes without prior positional data, mimicking self-assembly processes.

Contribution

It presents a novel agent-based model demonstrating self-assembly of networks through local interactions without relying on preexisting positional cues.

Findings

Emergence of robust network structures in simulations

Agents successfully detect and connect appropriate nodes

Analytical and simulation methods confirm network connectivity

Abstract

We propose a model to show the self-assembling of network-like structures between a set of nodes without using preexisting positional information or long-range attraction of the nodes. The model is based on Brownian agents that are capable of producing different local (chemical) information and respond to it in a non-linear manner. They solve two tasks in parallel: (i) the detection of the appropriate nodes, and (ii) the establishment of stable links between them. We present results of computer simulations that demonstrate the emergence of robust network structures and investigate the connectivity of the network by means of both analytical estimations and computer simulations. PACS: 05.65.+b, 89.75.Kd, 84.30.Bv, 87.18.Sn