Evolutionary Linguistics and Evolutionary Economics

  • Takashi HashimotoEmail author


Evolutionary linguistics is going to clarify the evolutionary process of language and evolutionary economics is clarifying the dynamics of economic phenomena. In this paper, we consider the relevance between these two fields. In evolutionary linguistics, the origin of language is thought of as the biological evolutionary process of language capacity of humans and the evolution of language the processes of complexification and structuralization of language structure. The evolutionary process of language forms a double loop dynamics among biological evolution, learning and cultural evolution. This double loop among these three adaptive dynamics ranging in large spatio-temporal scales characterizes language evolution as complex systems. The double loop dynamics can also be found in the origin and the evolution of economics. Thus, evolutionary linguistics and evolutionary economics can collaborate in understanding of complex evolutionary phenomena. The constructive approach is a useful tool to study such complex systems. Communicating the development of methodology and findings to understand such complex systems as language evolution and economic evolution may lead these two fields to fruitful synergism.


evolutionary linguistics evolution and origin of language double loop dynamics rule dynamics constructive approach 
A12 B41 B52 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Boweles, S. and H. Gintis (2004) “The evolution of strong reciprocity: cooperation in heterogeneous populations,” Theoretical Population Biology 65: 17–28.CrossRefGoogle Scholar
  2. Boweles, S. and H. Gintis (forthcoming) The Cooperative Species: Human Reciprocity and its Evolution.Google Scholar
  3. Camerer, C. F. (2003) Behavioral Game Theory: Experiments in Strategic Interaction, Princeton University Press, Princeton.Google Scholar
  4. Challet, D. and Y. C. Zhang (1997) “Emergence of cooperation and organization in an evolutionary game,” Physica A 246: 407–418.CrossRefGoogle Scholar
  5. Christiansen, M. H. and S. Kirby (eds) (2003), Language Evolution: The States of the Art, Oxford University Press, Oxford.Google Scholar
  6. Elman, J. L. (1990) “Finding structure in time,” Cognitive Science 14: 179–211.CrossRefGoogle Scholar
  7. Hashimoto, T. (2004) “What is the problem of language evolution? — from a constructive perspective” (in Japanese), in Proceedings of the 18th Annual Conference of the Japanese Society for Artificial Intelligence (CD-ROM).Google Scholar
  8. - (2002a) “Complex systems” (in Japanese), in K. Sugiyama, A. Nagata and A. Shimojima (eds) Knowledge Science, Kinokuniya Shoten, Tokyo, pp. 126–131.Google Scholar
  9. - (2002b) “The constructive approach” (in Japanese), in K. Sugiyama, A. Nagata and A. Shimojima (eds) Knowledge Science, Kinokuniya Shoten, Tokyo, pp. 132–135.Google Scholar
  10. Kaneko, K. (2004) What is Life?—A Constructive and Dynamical Systems Approach to Biological Sciences (in Japanese), University of Tokyo Press, Tokyo.Google Scholar
  11. - and T. Ikegami (1998) The Evolutionary Scenario of Complex Systems (in Japanese), Asakura Shoten, Tokyo.Google Scholar
  12. - and I. Tsuda (2000) Complex Systems: Chaos and Beyond—A Constructive Approach with Applications in Life Sciences, Springer, Berlin.Google Scholar
  13. Kirby, S. and J. Hurford (2002) “The emergence of linguistic structure: an overview of the iterated learning model,” in A. Cangelosi and D. Parisi (eds) Simulating the Evolution of Language, Springer Verlag, London, pp. 121–148.CrossRefGoogle Scholar
  14. Langton, C. G. (ed) (1988) Artificial Life, Addison Wesley, Reading.Google Scholar
  15. Sato, T. and T. Hashimoto (2006) “Dynamic social simulation with multi-agents having internal dynamics,” in K. Hashida and K. Nitta (eds) New Frontiers in Artificial Intelligence: Joint Proceeding of the 17th and 18th Annual Conferences of the Japanese Society for Artificial Intelligence, Springer, Berlin (in press).Google Scholar
  16. Sato, T., T. Hashimoto and S. Egashira (to be submitted) “Institutional consideration of micro-macro loop with multi-agent simulation.”Google Scholar
  17. Shinohara, S. (2002) “How does money emerge?—consideration of an experiment using hermit crabs” (in Japanese), Keizai Seminaa (Economics Seminar) 572: 85–90.Google Scholar
  18. Shiozawa, Y. (1999) “On the micro-macro loop” (in Japanese), Keizai Ronsou, Proceedings of Economic Papers of Kyoto University 164.5: 1–67.Google Scholar
  19. Tinbergen, N. (1963) “On aims and methods of ethology,” Zeitschrift für Tierpsychologie 20: 410–433.CrossRefGoogle Scholar
  20. von Neumann, J. (1966) Theory of Self-Reproducing Automata, (edited and completed by A. Burks), University of Illinois Press, Champaign.Google Scholar
  21. Witt, U. (1999) “Bioeconomics as economics from a Darwinian perspective,” Journal of Bioeconomics 1.1: 19–34.CrossRefGoogle Scholar
  22. Yarbrough, R. (2005) “Teaching bioeconomics,” Journal of Bioeconomics 7.1: 1–38.CrossRefGoogle Scholar

Copyright information

© Japan Association for Evolutionary Economics 2006

Authors and Affiliations

  1. 1.Japan Advanced Institute of Science and TechnologyIshikawaJapan

Personalised recommendations