What Makes a System Complex? an Approach to Self-Organization and Emergence

TL;DR

This paper explores the nature of system complexity, its states, and behaviors, emphasizing self-organization and emergence, with implications for designing intelligent, robust man-made systems inspired by natural processes.

Contribution

It introduces a classification of systems into simple, complicated, and complex states, analyzing their properties and the role of self-organization and emergence in complex systems.

Findings

Complex systems exhibit self-organization and emergent behaviors.

There are three main states of systems: simple, complicated, and complex.

Complexity involves a balance between system isolation and external interaction.

Abstract

The fast changing reality in technical and natural domains perceived by always more accurate observations has drawn attention on new and very broad class of systems with specific behaviour represented under the common wording complexity. From elementary system graph representation with components as nodes and interactions as vertices, systems are shown to belong to only three states : simple, complicated, and complex, the main properties of which are discussed. The first two states have been studied at length over past centuries, and last one finds its origin in the elementary fact that when system performance is pushed up, there exists a threshold above which interaction between components overtake outside interaction. Then system self-organizes and filters corresponding outer action, making it more robust to outer effect, with emergence of new behaviour not predictable from only components study. Examples in Physics and Biology are given. Three main classes of complexity behaviour are distinguished corresponding to different grades of difficulty to handle their dynamics. The interest of using complex state properties in man-made systems is stressed. Important issues concentrating on the difficult balance between relative system isolation when becoming complex and required delegation of corresponding new capability from (outside) operator are discussed. This implies giving the system some intelligence in an adequate frame between new augmented system state and supervising operator, with consequences on canonical system triplet {effector-sensor-controller} to be reorganized in this new setting. Moreover, entering complexity state opens the possibility for function to feedback onto structure, ie to mimic at technical level the invention of Nature over Her very long history.