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Two Notes on Replication in Evolutionary Modelling

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Author Info
Riechmann, Thomas

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Abstract

Replicator dynamics and replication as used in evolutionary algorithms are, due to their most basic forms, structurally the same. This short note will prove this thesis. Although this finding is clear cut and easy to show, it is of great importance for the not yet united families of game theorists on the one hand and evolutionary programmers on the other, meaning that it is perfectly legal and correct to mutually use the tools and findings of each other.

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Publisher Info
Paper provided by Universität Hannover, Wirtschaftswissenschaftliche Fakultät in its series Diskussionspapiere der Wirtschaftswissenschaftlichen Fakultät der Universität Hannover with number dp-239.

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Length: 17 pages
Date of creation: Mar 2001
Date of revision:
Handle: RePEc:han:dpaper:dp-239

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Find related papers by JEL classification:
C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games

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.:

  1. Fudenberg, Drew & Levine, David, 1998. "Learning in games," European Economic Review, Elsevier, vol. 42(3-5), pages 631-639, May. [Downloadable!] (restricted)
  2. Jack Hirshleifer & Juan Carlos Martinez Coll, 1992. "Selection, Mutation, and the Preservation of Diversity in Evolutionary Games," UCLA Economics Working Papers 648, UCLA Department of Economics. [Downloadable!]
  3. repec:att:wimass:199325 is not listed on IDEAS
  4. Thomas Riechmann, 2001. "Evolutionary Learning in the Ultimatum Game," Computing in Economics and Finance 2001 91, Society for Computational Economics.
  5. repec:att:wimass:199323 is not listed on IDEAS
  6. Arifovic, Jasmina, 1994. "Genetic algorithm learning and the cobweb model," Journal of Economic Dynamics and Control, Elsevier, vol. 18(1), pages 3-28, January. [Downloadable!] (restricted)
  7. Thomas Riechmann, 1999. "Learning and behavioral stability An economic interpretation of genetic algorithms," Journal of Evolutionary Economics, Springer, vol. 9(2), pages 225-242. [Downloadable!] (restricted)
    Other versions:
  8. Riechmann, Thomas, 2001. "Genetic algorithm learning and evolutionary games," Journal of Economic Dynamics and Control, Elsevier, vol. 25(6-7), pages 1019-1037, June. [Downloadable!] (restricted)
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Cited by:
(explanations, 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.)

  1. Riechmann, Thomas, 2002. "Cournot or Walras? Agent Based Learning, Rationality, and Long Run Results in Oligopoly Games," Diskussionspapiere der Wirtschaftswissenschaftlichen Fakultät der Universität Hannover dp-261, Universität Hannover, Wirtschaftswissenschaftliche Fakultät. [Downloadable!]
  2. Ian McCarthy, 2008. "Simulating Sequential Search Models with Genetic Algorithms: Analysis of Price Ceilings, Taxes, Advertising and Welfare," Caepr Working Papers 2008-010, Center for Applied Economics and Policy Research, Economics Department, Indiana University Bloomington. [Downloadable!]
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This page was last updated on 2009-12-3.

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