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A model of learning and emulation with artificial adaptive agents

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Author Info
James Bullard
John Duffy

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Abstract

We study adaptive learning behavior in a sequence of n-period endowment overlapping generations economies with fiat currency, where n refers to the number of periods in agents' lifetimes. Agents initially have heterogeneous beliefs and seek to form multi-step-ahead forecasts of future prices using a forecast rule chosen from a vast set of possible forecast rules. Agents take optimal actions given their forecasts of future prices. They learn in every period by creating new forecast rules and by emulating the forecast rules of other agents. Computational experiments with artificial adaptive agents are conducted. These experiments yield three qualitatively different types of outcomes. In one, the initially heterogeneous population of artificial agents learns to coordinate on a low inflation, stationary perfect foresight equilibrium. In another, we observe persistent currency collapse. The third outcome is a lack of coordination within the allotted time frame. One possible outcome, a stationary perfect foresight equilibrium with a relatively high inflation rate, is never observed.

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Paper provided by Federal Reserve Bank of St. Louis in its series Working Papers with number 1994-014.

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Date of creation: 1994
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Publication status: Published in Journal of Economic Dynamics and Control, February 1998
Handle: RePEc:fip:fedlwp:1994-014

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Keywords: Consumption (Economics);

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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. 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. [Downloadable!] (restricted)
  2. Andreoni James & Miller John H., 1995. "Auctions with Artificial Adaptive Agents," Games and Economic Behavior, Elsevier, vol. 10(1), pages 39-64, July. [Downloadable!] (restricted)
  3. Binmore, K. & Samuelson, L., 1990. "Evolutionary Stability In Repeated Games Played By Finite Automata," Working papers 90-29, Wisconsin Madison - Social Systems.
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  4. George W. Evans & Garey Ramey, 1995. "Calculation, Adaptation, and Rational Expectations," University of California at San Diego, Economics Working Paper Series 95-10, Department of Economics, UC San Diego.
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  5. Arifovic, Jasmina, 1995. "Genetic algorithms and inflationary economies," Journal of Monetary Economics, Elsevier, vol. 36(1), pages 219-243, August. [Downloadable!] (restricted)
  6. 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. [Downloadable!] (restricted)
  7. Binmore, Kenneth G. & Samuelson, Larry, 1992. "Evolutionary stability in repeated games played by finite automata," Journal of Economic Theory, Elsevier, vol. 57(2), pages 278-305, August. [Downloadable!] (restricted)
  8. repec:cup:cbooks:9780521479479 is not listed on IDEAS
  9. 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. [Downloadable!] (restricted)
  10. 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)
  11. George W. Evans & Garey Ramey, 1992. "Expectation Calculation, Hyperinflation and Currency Collapse," University of California at San Diego, Economics Working Paper Series 92-17, Department of Economics, UC San Diego.
  12. Ho, Teck-Hua, 1996. "Finite automata play repeated prisoner's dilemma with information processing costs," Journal of Economic Dynamics and Control, Elsevier, vol. 20(1-3), pages 173-207. [Downloadable!] (restricted)
  13. Arthur, W Brian, 1994. "Inductive Reasoning and Bounded Rationality," American Economic Review, American Economic Association, vol. 84(2), pages 406-11, May. [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. Orlando Gomes, . "Volatility, Heterogeneous Agents and Chaos," The Electronic Journal of Evolutionary Modeling and Economic Dynamics, IFReDE - Université Montesquieu Bordeaux IV. [Downloadable!]
    Other versions:
  2. James Bullard & John Duffy, 1994. "Using genetic algorithms to model the evolution of heterogeneous beliefs," Working Papers 1994-028, Federal Reserve Bank of St. Louis. [Downloadable!]
    Other versions:
  3. Leigh Tesfatsion, 1998. "Teaching Agent-Based Computational Economics to Graduate Students," Computational Economics 9809001, EconWPA, revised 16 Nov 1998. [Downloadable!]
    Other versions:
  4. M. Utku Unver, 2001. "Internet Auctions with Artificial Adaptive Agents," Computing in Economics and Finance 2001 38, Society for Computational Economics. [Downloadable!]
  5. James Bullard & Jasmina Arifovic & John Duffy, 1995. "Learning in a model of economic growth and development," Working Papers 1995-017, Federal Reserve Bank of St. Louis. [Downloadable!]
  6. Shu-Heng Chen & Chia-Hsuan Yeh, 1999. "Evolving Traders and the Faculty of the Business School: A New Architecture of the Artificial Stock Market," Computing in Economics and Finance 1999 613, Society for Computational Economics. [Downloadable!]
  7. Riechmann, Thomas, 1997. "Learning and Behavoiral Stability - An Economic Interpretation of Genetic Algorithms," Diskussionspapiere der Wirtschaftswissenschaftlichen Fakultät der Universität Hannover dp-209, Universität Hannover, Wirtschaftswissenschaftliche Fakultät. [Downloadable!]
    Other versions:
  8. Leigh TESFATSION, 1995. "How Economists Can Get Alife," Economic Report 37, Iowa State University Department of Economics. [Downloadable!]
  9. John Duffy, 2004. "Agent-Based Models and Human Subject Experiments," Computational Economics 0412001, EconWPA. [Downloadable!]
    Other versions:
  10. Smith, Peter, 2004. "Reworking the Standard Model of Competitive Markets: The Role of Fuzzy Logic and Genetic Algorithms in Modelling Complex Non-Linear Economic System," General Discussion Papers 30569, University of Manchester, Institute for Development Policy and Management (IDPM). [Downloadable!]
  11. Shu-Heng Chen, John Duffy, Chia-Hsuan Yeh, . "Equilibrium Selection via Adaptation: Using Genetic Programming to Model Learning in a Coordination Game," The Electronic Journal of Evolutionary Modeling and Economic Dynamics, IFReDE - Université Montesquieu Bordeaux IV. [Downloadable!]
  12. Marco Casari, 2003. "Does bounded rationality lead to individual heterogeneity? The impact of the experimentation process and of memory constraints," UFAE and IAE Working Papers 583.03, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC). [Downloadable!]
  13. Marco Casari, 2004. "Can Genetic Algorithms Explain Experimental Anomalies?," Computational Economics, Springer, vol. 24(3), pages 257-275, March. [Downloadable!] (restricted)
  14. Marco Casari, 2002. "Can genetic algorithms explain experimental anomalies? An application to common property resources," UFAE and IAE Working Papers 542.02, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC). [Downloadable!]
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