Using Genetic Algorithms to Model the Evolution of Heterogeneous Beliefs
We study a general equilibrium system where agents have heterogeneous beliefs concerning realizations of possible outcomes. The actual outcomes feed back into beliefs thus creating a complicated nonlinear system. Beliefs are updated via a genetic algorithm learning process which we interpret as representing communication among agents in the economy. We are able to illustrate a simple principle: genetic algorithms can be implemented so that they represent pure learning effects (i.e., beliefs updating based on realizations of endogenous variables in an environment with heterogeneous beliefs). Agents optimally solve their maximization problem at each date given their beliefs at each date. We report the results of a set of computational experiments in which we find that our population of artificial adaptive agents is usually able to coordinate their beliefs so as to achieve the Pareto superior rational expectations equilibrium of the model. Citation Copyright 1999 by Kluwer Academic Publishers.
Volume (Year): 13 (1999)
Issue (Month): 1 (February)
|Contact details of provider:|| Web page: http://www.springerlink.com/link.asp?id=100248|
More information through EDIRC
References listed on IDEAS
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.:
- Thomas J. Sargent & Neil Wallace, 1981. "Some unpleasant monetarist arithmetic," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Fall.
- James Bullard, 1991.
1991-004, Federal Reserve Bank of St. Louis.
- Routledge, Bryan R, 1999. "Adaptive Learning in Financial Markets," Review of Financial Studies, Society for Financial Studies, vol. 12(5), pages 1165-1202.
- Arifovic, Jasmina, 1995. "Genetic algorithms and inflationary economies," Journal of Monetary Economics, Elsevier, vol. 36(1), pages 219-243, August.
- Marimon, Ramon & Sunder, Shyam, 1994.
"Expectations and Learning under Alternative Monetary Regimes: An Experimental Approach,"
Springer, vol. 4(1), pages 131-62, January.
- Marimon, R. & Sunder, S., 1993. "Expectations and Learning under Alternative Monetary Regimes: An Experimental Approach," Papers 189, Cambridge - Risk, Information & Quantity Signals.
- Ramon Marimon & Shyam Sunder, 1993. "Expectations and learning under alternative monetary regimes: An experimental approach," Economics Working Papers 37, Department of Economics and Business, Universitat Pompeu Fabra.
- Arifovic, Jasmina & Eaton, Curtis, 1995.
"Coordination via Genetic Learning,"
Society for Computational Economics, vol. 8(3), pages 181-203, August.
- 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.
- Arifovic, Jasmina & Bullard, James & Duffy, John, 1997. " The Transition from Stagnation to Growth: An Adaptive Learning Approach," Journal of Economic Growth, Springer, vol. 2(2), pages 185-209, July.
- 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 Bullard & John Duffy, 1994. "A model of learning and emulation with artificial adaptive agents," Working Papers 1994-014, Federal Reserve Bank of St. Louis.
- James Bullard & John Duffy, 1995. "On learning and the stability of cycles," Working Papers 1995-006, Federal Reserve Bank of St. Louis.
- Arifovic, Jasmina, 1994. "Genetic algorithm learning and the cobweb model," Journal of Economic Dynamics and Control, Elsevier, vol. 18(1), pages 3-28, January.
When requesting a correction, please mention this item's handle: RePEc:kap:compec:v:13:y:1999:i:1:p:41-60. 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: (Guenther Eichhorn)or (Christopher F. Baum)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.