An information‐theoretic primer on complexity, self‐organization, and emergence

TLDR

Complex Systems Science seeks to understand complexity, self‑organization, emergence, and adaptation, but fuzzy definitions and unclear relationships among these processes lead to miscommunication across disciplines. The authors propose a set of concepts and their information‑theoretic interpretations to facilitate discourse in Complex Systems Science. They develop a framework of concepts and corresponding information‑theoretic interpretations to clarify the relationships among complexity, self‑organization, emergence, and adaptation. The suggested baseline is expected to promote consistent communication among practitioners and yield new insights into the field. Published 2008 Wiley Periodicals, Inc., Complexity, 2009.

Abstract

Abstract Complex Systems Science aims to understand concepts like complexity, self‐organization, emergence and adaptation, among others. The inherent fuzziness in complex systems definitions is complicated by the unclear relation among these central processes: does self‐organisation emerge or does it set the preconditions for emergence? Does complexity arise by adaptation or is complexity necessary for adaptation to arise? The inevitable consequence of the current impasse is miscommunication among scientists within and across disciplines. We propose a set of concepts, together with their possible information‐theoretic interpretations, which can be used to facilitate the Complex Systems Science discourse. Our hope is that the suggested information‐theoretic baseline may promote consistent communications among practitioners, and provide new insights into the field. Published 2008 Wiley Periodicals, Inc. Complexity, 2009