Three Myths in Complexity Science and How to Resolve Them

TL;DR

This paper debunks three myths in complexity science, clarifies essential definitions, and offers a contemporary interpretation to advance understanding of complex systems.

Contribution

It provides a new interpretation of complex systems and clarifies key definitions, addressing misconceptions in the field.

Findings

Debunking of three common myths in complexity science

Proposed resolutions for misconceptions in complex systems

A contemporary framework for understanding complex systems

Abstract

From bird flocking to neural dynamics, complex systems generate fascinating structures and correlations. Often, seemingly simple dynamics lead to intricate emergent properties. Despite their visceral appeal, defining complex systems lacks universal agreement. In this paper, I will debunk three prevalent myths in complex systems and propose resolutions. This work contributes by offering a contemporary interpretation of complex systems, presenting essential definitions that benefit complexity scientists.