Tentative guidelines for the implementation of meta-structural and network software models of collective behaviours

TL;DR

This paper provides practical guidelines for implementing meta-structural and network models to analyze, induce, and maintain collective behaviors, focusing on simulated agents and properties like coherence and scale invariance.

Contribution

It introduces specific guidelines for software implementation of meta-structure models, including identifying mesoscopic variables and properties for collective behavior analysis and control.

Findings

Guidelines for identifying mesoscopic variables and meta-structural properties.

Proposals for inducing coherence in non-coherent behaviors.

Comments on network models and properties like topological distances.

Abstract

We present some practical guidelines for software implementations of the meta-structure project introduced in previous contributions. The purpose of the meta-structure project is to implement models not only to detect, but also to induce, change and maintain properties acquired by collective behaviours. We consider the simplified case given by simulated collective behaviours where all the microscopic spatial information (x, y, z) for each interacting agent per instant are available ex-post in a suitable file. In particular, we introduce guidelines to identify suitable mesoscopic variables (clusters) and meta-structural properties suitable for representing coherence of collective behaviours to be also used to induce coherence in non-coherent Brownian behaviours. Furthermore, on the basis of previous contributions which studied in real flocks properties related to topological distances as topological ranges of interaction and scale invariance, here we introduce some comments and proposals to be further studied and implemented for network models of collective behaviours. Keywords: Cluster, Coherence, Ergodicity, Mesoscopic, Meta-Structure, Network, Threshold.