Learning and Behavoiral Stability - An Economic Interpretation of Genetic Algorithms
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.
|Date of creation:||Oct 1997|
|Contact details of provider:|| Postal: Koenigsworther Platz 1, D-30167 Hannover|
Phone: (0511) 762-5350
Fax: (0511) 762-5665
Web page: http://www.wiwi.uni-hannover.de
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Arifovic, Jasmina, 1994. "Genetic algorithm learning and the cobweb model," Journal of Economic Dynamics and Control, Elsevier, vol. 18(1), pages 3-28, January.
- 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.
- Lucas, Robert E, Jr, 1986. "Adaptive Behavior and Economic Theory," The Journal of Business, University of Chicago Press, vol. 59(4), pages 401-426, October.
- Hayek, F. A., 2012. "New Studies in Philosophy, Politics, Economics, and the History of Ideas," University of Chicago Press Economics Books, University of Chicago Press, number 9780226321288, April.
- Bullard, James & Duffy, John, 1998.
"A model of learning and emulation with artificial adaptive agents,"
Journal of Economic Dynamics and Control,
Elsevier, vol. 22(2), pages 179-207, February.
- James B. Bullard & John Duffy, 1994. "A model of learning and emulation with artificial adaptive agents," Working Papers 1994-014, Federal Reserve Bank of St. Louis.
- Birchenhall, Chris, 1995. "Modular Technical Change and Genetic Algorithms," Computational Economics, Springer;Society for Computational Economics, vol. 8(3), pages 233-253, August.
- Chris Birchenhall & Nikos Kastrinos & Stan Metcalfe, 1997. "Genetic algorithms in evolutionary modelling," Journal of Evolutionary Economics, Springer, vol. 7(4), pages 375-393.
- Andreoni James & Miller John H., 1995. "Auctions with Artificial Adaptive Agents," Games and Economic Behavior, Elsevier, vol. 10(1), pages 39-64, July.
- Riechmann, Thomas, 2001. "Genetic algorithm learning and evolutionary games," Journal of Economic Dynamics and Control, Elsevier, vol. 25(6-7), pages 1019-1037, June.
- 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 510-541, June.
- Blume, Lawrence E. & Easley, David, 1993. "Economic natural selection," Economics Letters, Elsevier, vol. 42(2-3), pages 281-289. Full references (including those not matched with items on IDEAS)
When requesting a correction, please mention this item's handle: RePEc:han:dpaper:dp-209. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Heidrich, Christian)
If references are entirely missing, you can add them using this form.