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On Designing Economic Agents That Behave Like Human Agents

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Author Info
Arthur, W Brian
Abstract

This paper explores the idea of constructing theoretical economic agents that behave like actual human agents and using them in neoclassical economic models. It does this in a repeated-choice setting by postulating "artificial agents" who use a learning algorithm calibrated against human learning data from psychological experiments. The resulting calibrated algorithm appears to replicate human learning behavior to a high degree and reproduces several "stylized facts" of learning. It can, therefore, be used to replace the idealized, perfectly rational agents in appropriate neoclassical models with "calibrated agents" that represent actual human behavior. The paper discusses the possibilities of using the algorithm to represent human learning in normal-form stage games and in more general neoclassical models in economics. It explores the likelihood of convergence to long-run optimality and to Nash behavior, and the "characteristic learning time" implicit in human adaptation in the economy.

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Publisher Info
Article provided by Springer in its journal Journal of Evolutionary Economics.

Volume (Year): 3 (1993)
Issue (Month): 1 (February)
Pages: 1-22
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Handle: RePEc:spr:joevec:v:3:y:1993:i:1:p:1-22

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  1. M. Keilbach & M. Posch, 1998. "Network Externalities and the Dynamics of Markets," Working Papers ir98089, International Institute for Applied Systems Analysis. [Downloadable!]
  2. Tomas Klos, 1999. "Governance and Matching," Computing in Economics and Finance 1999 341, Society for Computational Economics. [Downloadable!]
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  3. Clemens, Christiane & Riechmann, Thomas, 1996. "Evolutionäre Optimierungsverfahren und ihr Einsatz in der ökonomischen Forschung," Diskussionspapiere der Wirtschaftswissenschaftlichen Fakultät der Universität Hannover dp-195, Universität Hannover, Wirtschaftswissenschaftliche Fakultät. [Downloadable!]
  4. Ed Hopkins, 2004. "Two Competing Models of How People Learn in Games," ESE Discussion Papers 51, Edinburgh School of Economics, University of Edinburgh. [Downloadable!]
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  5. Tony Curson Price, 1997. "Using co-evolutionary programming to simulate strategic behaviour in markets," Levine's Working Paper Archive 588, UCLA Department of Economics. [Downloadable!]
  6. Stéphanie LAVIGNE (ESC Toulouse and GRES-LEREPS), 2004. "Modelling an artificial stock market: When cognitive institutions influence market dynamics," Working Papers of GRES - Cahiers du GRES 2004-04, Groupement de Recherches Economiques et Sociales. [Downloadable!]
  7. Rustichini, A., 1998. "Sophisticated players and sophisticated agents," Discussion Paper 110, Tilburg University, Center for Economic Research. [Downloadable!]
  8. Jonathan Bendor & Dilip Mookherjee & Debraj Ray, 2001. "Reinforcement Learning in Repeated Interaction Games," Advances in Theoretical Economics, Berkeley Electronic Press, vol. 1(advances/), pages 1008-1008. [Downloadable!] (restricted)
  9. Max Keilbach, 1999. "Network Externalities and the Path Dependence of Markets: Will Bill Gates Make It?," Computing in Economics and Finance 1999 711, Society for Computational Economics.
  10. Dr Jason Potts, 2000. "Evolutionary Microeconomics and the Theory of Expectations," Discussion Papers Series 270, School of Economics, University of Queensland, Australia. [Downloadable!]
  11. Ed Hopkins, 2004. "Adaptive Learning Models of Consumer Behaviour," ESE Discussion Papers 121, Edinburgh School of Economics, University of Edinburgh. [Downloadable!]
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  12. Leigh TESFATSION, 1995. "How Economists Can Get Alife," Economic Report 37, Iowa State University Department of Economics. [Downloadable!]
  13. Ed Hopkins, 2004. "Adaptative Learning Models of Consumer Behaviour (first version)," ESE Discussion Papers 80, Edinburgh School of Economics, University of Edinburgh.
  14. Martin Lettau & Harald Uhlig, 1999. "Rules of Thumb versus Dynamic Programming," American Economic Review, American Economic Association, vol. 89(1), pages 148-174, March. [Downloadable!] (restricted)
  15. John Duffy, 2004. "Agent-Based Models and Human Subject Experiments," Computational Economics 0412001, EconWPA. [Downloadable!]
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  16. Possajennikov, A., 1997. "An analysis of a simple reinforcing dynamics : learning to play an "egalitarian" equilibrium," Discussion Paper 19, Tilburg University, Center for Economic Research. [Downloadable!]
  17. Leigh Tesfatsion, 1998. "Teaching Agent-Based Computational Economics to Graduate Students," Computational Economics 9809001, EconWPA, revised 16 Nov 1998. [Downloadable!]
  18. Gorobets, A. & Nooteboom, B., 2004. "Agent based computational model of trust," Research Paper ERS-2004-108-ORG Revision, 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 Uni. [Downloadable!]
  19. A. Bassanini, 1997. "Localized Technological Change and Path-Dependent Growth," Working Papers ir97086, International Institute for Applied Systems Analysis. [Downloadable!]
  20. Patalano Roberta, 2003. "Beyond rationality: images as guide-lines to choice," CESMEP Working Papers 200305, University of Turin. [Downloadable!]
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