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Evolutionäre Optimierungsverfahren und ihr Einsatz in der ökonomischen Forschung

  • Clemens, Christiane
  • Riechmann, Thomas

Dieser Beitrag bietet eine Einführung in eine Gruppe moderner Algorithmen, den sogenannten evolutionären Optimierungsverfahren. Anhand eines einfachen Beispiels wird die grundsätzliche Funktionsweise dieser Algorithmen skizziert. Darüberhinaus wird ein Überblick über die Anwendungsmöglichkeiten dieser Verfahren innerhalb der ökonomischen Forschung - insbesondere im Bereich der Modellierung von Lernprozessen - gegeben.

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Paper provided by Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät in its series Hannover Economic Papers (HEP) with number dp-195.

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Length: 24 pages
Date of creation: Jun 1996
Date of revision:
Handle: RePEc:han:dpaper:dp-195
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  1. Kiyotaki, Nobuhiro & Wright, Randall, 1989. "On Money as a Medium of Exchange," Journal of Political Economy, University of Chicago Press, vol. 97(4), pages 927-54, August.
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  6. Marimon, Ramon & McGrattan, Ellen & Sargent, Thomas J., 1990. "Money as a medium of exchange in an economy with artificially intelligent agents," Journal of Economic Dynamics and Control, Elsevier, vol. 14(2), pages 329-373, May.
  7. Eaton, C. & White, W.D., 1992. "Image Building," Discussion Papers dp92-17, Department of Economics, Simon Fraser University.
  8. Arifovic, Jasmina, 1994. "Genetic algorithm learning and the cobweb model," Journal of Economic Dynamics and Control, Elsevier, vol. 18(1), pages 3-28, January.
  9. Tesfatsion, Leigh, 1995. "How to Get Alife," Staff General Research Papers 10546, Iowa State University, Department of Economics.
  10. Hirshleifer, Jack, 1977. "Economics from a Biological Viewpoint," Journal of Law and Economics, University of Chicago Press, vol. 20(1), pages 1-52, April.
  11. Jack Hirshleifer, 1977. "Economics from a Biological Viewpoint," UCLA Economics Working Papers 087, UCLA Department of Economics.
  12. Beaumont, Paul M & Bradshaw, Patrick T, 1995. "A Distributed Parallel Genetic Algorithm for Solving Optimal Growth Models," Computational Economics, Society for Computational Economics, vol. 8(3), pages 159-79, August.
  13. Arifovic, J. & Eaton, C., 1994. "Coordination via Genetic Learning," Discussion Papers dp94-11, Department of Economics, Simon Fraser University.
  14. 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.
  15. Holland, John H & Miller, John H, 1991. "Artificial Adaptive Agents in Economic Theory," American Economic Review, American Economic Association, vol. 81(2), pages 365-71, May.
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