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Learning and Behavoiral Stability - An Economic Interpretation of Genetic Algorithms

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  • Riechmann, Thomas

Abstract

This article tries to connect two separate strands of literature concerning genetic algorithms. On the one hand, extensive research took place in mathematics and closely related sciences in order to find out more about the properties of genetic algorithms as stochastic processes. On the other hand, recent economic literature uses genetic algorithms as a metaphor for social learning. This paper will face the question what an economist can learn from the mathematical branch of research, especially concerning the convergence and stability properties of the genetic algorithm. It is shown that genetic algorithm learning is a compound of three different learning schemes. First, every particular scheme is analyzed. Then it will be pointed out that it is the combination of the three schemes that gives genetic algorithm learning its special flair: A kind of stability somewhere in between asymptotic convergence and explosion.

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File URL: http://diskussionspapiere.wiwi.uni-hannover.de/pdf_bib/dp-209.pdf
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Bibliographic Info

Paper provided by Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät in its series Hannover Economic Papers (HEP) with number dp-209.

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Length: 22 pages
Date of creation: Oct 1997
Date of revision:
Handle: RePEc:han:dpaper:dp-209

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Related research

Keywords: Learning; Computational economics; Genetic algorithms; Markov process; Evolutionary dynamics;

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References

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  1. Andreoni James & Miller John H., 1995. "Auctions with Artificial Adaptive Agents," Games and Economic Behavior, Elsevier, vol. 10(1), pages 39-64, July.
  2. James Bullard & John Duffy, 1994. "A model of learning and emulation with artificial adaptive agents," Working Papers 1994-014, Federal Reserve Bank of St. Louis.
  3. Lucas, Robert E, Jr, 1986. "Adaptive Behavior and Economic Theory," The Journal of Business, University of Chicago Press, vol. 59(4), pages S401-26, October.
  4. Chris Birchenhall & Nikos Kastrinos & Stan Metcalfe, 1997. "Genetic algorithms in evolutionary modelling," Journal of Evolutionary Economics, Springer, vol. 7(4), pages 375-393.
  5. Riechmann, Thomas, 2001. "Genetic algorithm learning and evolutionary games," Journal of Economic Dynamics and Control, Elsevier, vol. 25(6-7), pages 1019-1037, June.
  6. Clemens, Christiane & Riechmann, Thomas, 1996. "Evolutionäre Optimierungsverfahren und ihr Einsatz in der ökonomischen Forschung," Hannover Economic Papers (HEP) dp-195, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
  7. Arifovic, Jasmina, 1994. "Genetic algorithm learning and the cobweb model," Journal of Economic Dynamics and Control, Elsevier, vol. 18(1), pages 3-28, January.
  8. Blume, Lawrence E. & Easley, David, 1993. "Economic natural selection," Economics Letters, Elsevier, vol. 42(2-3), pages 281-289.
  9. Arifovic, Jasmina, 1996. "The Behavior of the Exchange Rate in the Genetic Algorithm and Experimental Economies," Journal of Political Economy, University of Chicago Press, vol. 104(3), pages 510-41, June.
  10. Birchenhall, Chris, 1995. "Modular Technical Change and Genetic Algorithms," Computational Economics, Society for Computational Economics, vol. 8(3), pages 233-53, August.
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