Advanced Search
MyIDEAS: Login to save this paper or follow this series

Economic Modeling Using Evolutionary Algorithms: The Effect of a Binary Encoding of Strategies

Contents:

Author Info

  • Waltman, L.
  • van Eck, N.J.P.
  • Dekker, R.
  • Kaymak, U.

Abstract

We are concerned with evolutionary algorithms that are employed for economic modeling purposes. We focus in particular on evolutionary algorithms that use a binary encoding of strategies. These algorithms, commonly referred to as genetic algorithms, are popular in agent-based computational economics research. In many studies, however, there is no clear reason for the use of a binary encoding of strategies. We therefore examine to what extent the use of such an encoding may influence the results produced by an evolutionary algorithm. It turns out that the use of a binary encoding can have quite significant effects. Since these effects do not have a meaningful economic interpretation, they should be regarded as artifacts. Our findings indicate that in general the use of a binary encoding is undesirable. They also highlight the importance of employing evolutionary algorithms with a sensible economic interpretation.

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL: http://repub.eur.nl/pub/16014/ERS-2009-028-LIS.pdf
Download Restriction: no

Bibliographic Info

Paper provided by Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam in its series ERIM Report Series Research in Management with number ERS-2009-028-LIS.

as in new window
Length:
Date of creation: 20 May 2009
Date of revision:
Handle: RePEc:ems:eureri:16014

Contact details of provider:
Postal: RSM Erasmus University & Erasmus School of Economics, PoBox 1738, 3000 DR Rotterdam
Phone: 31-10-408 1182
Fax: 31-10-408 9020
Email:
Web page: http://www.erim.eur.nl/
More information through EDIRC

Related research

Keywords: agent-based computational economics; binary encoding; evolutionary algorithm; genetic algorithm; premature convergence;

Other versions of this item:

Find related papers by JEL classification:

References

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.:
as in new window
  1. Andrew Sellgren, 2001. "The evolution of insurance markets under adverse selection," Journal of Evolutionary Economics, Springer, vol. 11(5), pages 501-526.
  2. Michael Kopel & Herbert Dawid, 1998. "On economic applications of the genetic algorithm: a model of the cobweb type," Journal of Evolutionary Economics, Springer, vol. 8(3), pages 297-315.
  3. Vriend, Nicolaas J., 2000. "An illustration of the essential difference between individual and social learning, and its consequences for computational analyses," Journal of Economic Dynamics and Control, Elsevier, vol. 24(1), pages 1-19, January.
  4. Arifovic, Jasmina, 1994. "Genetic algorithm learning and the cobweb model," Journal of Economic Dynamics and Control, Elsevier, vol. 18(1), pages 3-28, January.
  5. David van Bragt & Cees van Kemenade & Han La Poutre, 1999. "The Influence of Evolutionary Selection Schemes on the Iterated Prisoner's Dilemma," Computing in Economics and Finance 1999 344, Society for Computational Economics.
  6. Rhode, Paul & Stegeman, Mark, 1996. "Learning, Mutation, and Long-Run Equilibria in Games: A Comment," Econometrica, Econometric Society, vol. 64(2), pages 443-49, March.
  7. Brenner, Thomas, 2006. "Agent Learning Representation: Advice on Modelling Economic Learning," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 18, pages 895-947 Elsevier.
  8. Ernan Haruvy & Alvin E. Roth & M. Utku Unver, 2004. "The Dynamics of Law Clerk Matching: An Experimental and Computational Investigation of Proposals for Reform of the Market," Experimental 0404001, EconWPA.
  9. Schaffer, Mark E., 1989. "Are profit-maximisers the best survivors? : A Darwinian model of economic natural selection," Journal of Economic Behavior & Organization, Elsevier, vol. 12(1), pages 29-45, August.
  10. Floortje Alkemade & Han Poutré & Hans Amman, 2006. "Robust Evolutionary Algorithm Design for Socio-economic Simulation," Computational Economics, Society for Computational Economics, vol. 28(4), pages 355-370, November.
  11. Christiane Clemens & Thomas Riechmann, 2006. "Evolutionary Dynamics in Public Good Games," Computational Economics, Society for Computational Economics, vol. 28(4), pages 399-420, November.
  12. Yiping Xu, 2006. "The behavior of the exchange rate in the genetic algorithm with agents having long memory," Journal of Evolutionary Economics, Springer, vol. 16(3), pages 279-297, August.
  13. M. Utku �nver, 1999. "Backward Unraveling over Time: The Evolution of Strategic Behavior in the Entry-Level British Medical Labor Markets," Computing in Economics and Finance 1999 1132, Society for Computational Economics.
  14. Lux, Thomas & Schornstein, Sascha, 2003. "Genetic learning as an explanation of stylized facts of foreign exchange markets," Economics Working Papers |aEconomics working paper, Christian-Albrechts-University of Kiel, Department of Economics.
  15. Marks, R E, 1992. "Breeding Hybrid Strategies: Optimal Behaviour for Oligopolists," Journal of Evolutionary Economics, Springer, vol. 2(1), pages 17-38, March.
  16. 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.
  17. Edmund Chattoe-Brown, 1998. "Just How (Un)realistic Are Evolutionary Algorithms As Representations of Social Processes?," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 1(3), pages 2.
  18. Fernando Vega Redondo, 1996. "The evolution of walrasian behavior," Working Papers. Serie AD 1996-05, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
  19. Floortje Alkemade & Han Poutré & Hans Amman, 2009. "Robust Evolutionary Algorithm Design for Socio-Economic Simulation: A Correction," Computational Economics, Society for Computational Economics, vol. 33(1), pages 99-101, February.
  20. Miller, John H., 1996. "The coevolution of automata in the repeated Prisoner's Dilemma," Journal of Economic Behavior & Organization, Elsevier, vol. 29(1), pages 87-112, January.
  21. 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.
  22. Tony Curzon Price, 1997. "Using co-evolutionary programming to simulate strategic behaviour in markets," Journal of Evolutionary Economics, Springer, vol. 7(3), pages 219-254.
  23. Michael Maschek, 2010. "Intelligent Mutation Rate Control in an Economic Application of Genetic Algorithms," Computational Economics, Society for Computational Economics, vol. 35(1), pages 25-49, January.
  24. Tony Curson Price, 1997. "Using co-evolutionary programming to simulate strategic behaviour in markets," Levine's Working Paper Archive 588, David K. Levine.
  25. Jasmina Arifovic & Michael Maschek, 2006. "Revisiting Individual Evolutionary Learning in the Cobweb Model – An Illustration of the Virtual Spite-Effect," Computational Economics, Society for Computational Economics, vol. 28(4), pages 333-354, November.
  26. Enrico Gerding & David van Bragt & Han La Poutré, 2003. "Multi-Issue Negotiation Processes by Evolutionary Simulation, Validation and Social Extensions," Computational Economics, Society for Computational Economics, vol. 22(1), pages 39-63, August.
  27. Andreoni James & Miller John H., 1995. "Auctions with Artificial Adaptive Agents," Games and Economic Behavior, Elsevier, vol. 10(1), pages 39-64, July.
  28. Scott Wheeler & Nigel Bean & Janice Gaffney & Peter Taylor, 2006. "A Markov analysis of social learning and adaptation," Journal of Evolutionary Economics, Springer, vol. 16(3), pages 299-319, August.
  29. Thomas Riechmann, 2006. "Cournot or Walras? Long-Run Results in Oligopoly Games," Journal of Institutional and Theoretical Economics (JITE), Mohr Siebeck, Tübingen, vol. 162(4), pages 702-720, December.
  30. Hansen, Robert G. & Samuelson, William F., 1988. "Evolution in economic games," Journal of Economic Behavior & Organization, Elsevier, vol. 10(3), pages 315-338, October.
  31. Casari, Marco, 2008. "Markets in equilibrium with firms out of equilibrium: A simulation study," Journal of Economic Behavior & Organization, Elsevier, vol. 65(2), pages 261-276, February.
  32. Ludo Waltman & Nees Eck, 2009. "Robust Evolutionary Algorithm Design for Socio-Economic Simulation: Some Comments," Computational Economics, Society for Computational Economics, vol. 33(1), pages 103-105, February.
  33. Herbert Dawid & Joern Dermietzel, 2006. "How Robust is the Equal Split Norm? Responsive Strategies, Selection Mechanisms and the Need for Economic Interpretation of Simulation Parameters," Computational Economics, Society for Computational Economics, vol. 28(4), pages 371-397, November.
Full references (including those not matched with items on IDEAS)

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as in new window

Cited by:
  1. Isabelle Salle & Pascal Seppecher, 2013. "Social Learning about Consumption," Working Papers hal-00989233, HAL.

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:ems:eureri:16014. 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: (RePub).

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.