Functional Complexity Measure for Networks

TL;DR

This paper introduces a new complexity measure for networks that captures their functional flexibility by analyzing topological diversity, aiding in classifying networks based on their functionality.

Contribution

It proposes a novel complexity measure linking topological diversity to functional flexibility in networks, applicable to artificial and biological systems.

Findings

The measure reflects the functional flexibility of networks.

It enables classification of networks based on their topological diversity.

The approach is applicable to both artificial and biological networks.

Abstract

We propose a complexity measure which addresses the functional flexibility of networks. It is conjectured that the functional flexibility is reflected in the topological diversity of the assigned graphs, resulting from a resolution of their vertices and a rewiring of their edges under certain constraints. The application will be a classification of networks in artificial or biological systems, where functionality plays a central role.