Skip to main content

Complexity, Emergence, and Evolution

  • Chapter
  • First Online:
Economics for a Fairer Society
  • 403 Accesses

Abstract

Most economists are not familiar with complexity science as it applies to economics . Complexity and emergent behaviour are broad terms that are not scientifically defined. This chapter outlines how the terms complexity, emergent behaviour, and evolution are being used in this work. While mainly aimed at people who are not familiar with complexity, it also explains how these terms are specifically being used in this work. It also defines two new terms that clarify certain aspects of evolution as it applies to economics, specifically, the ‘fitness test’ and ‘evolutionary strength ’.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 44.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 59.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Arthur, W. B. (1989). Competing technologies, increasing returns, and lock-in by historical events. The Economic Journal, 99(394), 116–131.

    Google Scholar 

  • Bonabeau, E., Dorigo, M., & Theraulaz, G. (1999). Swarm intelligence: From natural to artificial systems (No. 1). New York: Oxford University Press.

    Google Scholar 

  • Chaos, J. G. (1988). Making a new science. Minerva: Minerva.

    Google Scholar 

  • Christen, M., & Franklin, L. R. (2002). The concept of emergence in complexity science: Finding coherence between theory and practice. In Proceedings of the Complex Systems Summer School (Vol. 4).

    Google Scholar 

  • Dessalles, J. L., & Phan, D. (2006). Emergence in multi-agent systems: Cognitive hierarchy, detection, and complexity reduction part I: Methodological issues. In Artificial Economics (pp. 147–159). Springer, Berlin: Heidelberg.

    Google Scholar 

  • Edmonds, B. (1995). What is complexity? The philosophy of complexity per se with application to some examples in evolution. In The evolution of complexity. Dordrecht: Kluwer Academic.

    Google Scholar 

  • Grassé, P. P. (1959). La reconstruction du nid et les coordinations interindividuelles chezBellicositermes natalensis etCubitermes sp. la théorie de la stigmergie: Essai d’interprétation du comportement des termites constructeurs. Insectes sociaux, 6(1), 41–80.

    Google Scholar 

  • Hillis, W. D. (1999). The pattern on the stone: The simple ideas that make computers work. New York: Basic Books (AZ).

    Google Scholar 

  • Hornby, G., Globus, A., Linden, D., & Lohn, J. (2006). Automated antenna design with evolutionary algorithms. In Space 2006 (p. 7242).

    Google Scholar 

  • John, G., Clements-Croome, D., & Jeronimidis, G. (2005). Sustainable building solutions: A review of lessons from the natural world. Building and Environment, 40(3), 319–328.

    Article  Google Scholar 

  • Johnson, S. (2001). Emergence: The connected lives of ants, brains, cities, and software. New York: Simon and Schuster.

    Google Scholar 

  • Lipson, H. (2005). Evolutionary robotics and open-ended design automation. Biomimetics, 17(9), 129–155.

    Article  Google Scholar 

  • Lucas, R. E. (1976, January). Econometric policy evaluation: A critique. In Carnegie-Rochester Conference Series on Public Policy (Vol. 1, pp. 19–46), North-Holland.

    Google Scholar 

  • Railsback, S. F., & Grimm, V. (2011). Agent-based and individual-based modeling: A practical introduction. Princeton: Princeton University Press.

    Google Scholar 

  • Santamaria-Bonfil, G., Gershenson, C., & Fernández, N. (2017). A package for measuring emergence, self-organization, and complexity based on Shannon entropy. Frontiers in Robotics and AI, 4, 10.

    Article  Google Scholar 

  • Schumpeter, J. A. (1912). Theorie der wirtschaftlichen Entwicklung (1st ed.) [English translation 1934: Theory of economic development. Cambridge, MA: Harvard University Press]. Leipzig: Duncker & Humblot.

    Google Scholar 

  • Standish, R. K. (2001). On complexity and emergence. arXiv preprint nlin/0101006.

    Google Scholar 

  • Veblen, T. (1898). Why is economics not an evolutionary science? The Quarterly Journal of Economics, 12(4), 373–397.

    Article  Google Scholar 

  • Wilensky, U., & Rand, W. (2015). An introduction to agent-based modeling: Modeling natural, social, and engineered complex systems with Netlogo. Cambridge: MIT Press.

    Google Scholar 

  • Witt, U. (2008). What is specific about evolutionary economics? Journal of Evolutionary Economics, 18(5), 547–575.

    Article  Google Scholar 

  • Zykov, V., Mytilinaios, E., Adams, B., & Lipson, H. (2005). Robotics: Self-reproducing machines. Nature, 435(7039), 163.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2019 The Author(s)

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Gooding, T. (2019). Complexity, Emergence, and Evolution. In: Economics for a Fairer Society. Palgrave Pivot, Cham. https://doi.org/10.1007/978-3-030-17020-2_3

Download citation

Publish with us

Policies and ethics