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

Mikhail Prokopenko*, Fabio Boschetti, Alex J. Ryan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

183 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)11-28
Number of pages18
Issue number1
Publication statusPublished - Sep 2009
Externally publishedYes


  • Adaptation
  • Assortativeness
  • Complexity
  • Emergence
  • Entropy rate
  • Excess entropy
  • Information theory
  • Predictive efficiency
  • Predictive information
  • Self-organization


Dive into the research topics of 'An information-theoretic primer on complexity, self-organization, and emergence'. Together they form a unique fingerprint.

Cite this