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Norms as emergent properties of adaptive learning: The case of economic routines

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  • Marco Valente

    (Aalborg University, Aalborg, Denmark)

  • Andrea Bassanini

    (Faculty of Statistics, University "La Sapienza", Rome, Italy, and OECD, Paris, France)

  • Luigi Marengo

    ()
    (Department of Economics, University of Trento, Via Inama 1, I-38100 Trento, Italy)

  • Giovanni Dosi

    (Scvola Superiore S. Anna, Pisa, Italy)

Abstract

Interaction among autonomous decision-makers is usually modelled in economics in game-theoretic terms or within the framework of General Equilibrium. Game-theoretic and General Equilibrium models deal almost exclusively with the existence of equilibria and do not analyse the processes which might lead to them. Even when existence proofs can be given, two questions are still open. The first concerns the possibility of multiple equilibria, which game theory has shown to be the case even in very simple models and which makes the outcome of interaction unpredictable. The second relates to the computability and complexity of the decision procedures which agents should adopt and questions the possibility of reaching an equilibrium by means of an algorithmically implementable strategy. Some theorems have recently proved that in many economically relevant problems equilibria are not computable. A different approach to the problem of strategic interaction is a "constructivist" one. Such a perspective, instead of being based upon an axiomatic view of human behaviour grounded on the principle of optimisation, focuses on algorithmically implementable "satisfycing" decision procedures. Once the axiomatic approach has been abandoned, decision procedures cannot be deduced from rationality assumptions, but must be the evolving outcome of a process of learning and adaptation to the particular environment in which the decision must be made. This paper considers one of the most recently proposed adaptive learning models: Genetic Programming and applies it to one the mostly studied and still controversial economic interaction environment, that of oligopolistic markets. Genetic Programming evolves decision procedures, represented by elements in the space of functions, balancing the exploitation of knowledge previously obtained with the search of more productive procedures. The results obtained are consistent with the evidence from the observation of the behaviour of real economic agents.

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Bibliographic Info

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

Volume (Year): 9 (1999)
Issue (Month): 1 ()
Pages: 5-26

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Handle: RePEc:spr:joevec:v:9:y:1999:i:1:p:5-26

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Related research

Keywords: Computability ; Genetic Programming ; Oligopoly;

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Cited by:
  1. Peter Abell & Teppo Felin & Nicolai Foss, 2007. "Building Micro-Foundations for the Routines, Capabilities, and Performance Links," DRUID Working Papers 07-02, DRUID, Copenhagen Business School, Department of Industrial Economics and Strategy/Aalborg University, Department of Business Studies.
  2. Ballot, Gerard & Taymaz, Erol, 2001. "Training policies and economic growth in an evolutionary world," Structural Change and Economic Dynamics, Elsevier, vol. 12(3), pages 311-329, September.
  3. Elizabeth Webster, 2004. "Firms' decisions to innovate and innovation routines," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 13(8), pages 733-745.
  4. Tanya Araújo & Miguel St. Aubyn, 2008. "Education, Neighborhood Effects And Growth: An Agent-Based Model Approach," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 11(01), pages 99-117.
  5. Murat YILDIZOGLU (Université Aix-Marseille3), 2009. "Evolutionary approaches of economic dynamics (In French)," Cahiers du GREThA 2009-16, Groupe de Recherche en Economie Théorique et Appliquée.
  6. Windrum,Paul, 1999. "Simulation models of technological innovation: A Review," Research Memorandum 005, Maastricht University, Maastricht Economic Research Institute on Innovation and Technology (MERIT).
  7. Teppo Felin & Nicolai Foss, 2006. "Individuals and Organizations Thoughts on a Micro-Foundations Project for Strategic Management and Organizational Analysis," DRUID Working Papers 06-01, DRUID, Copenhagen Business School, Department of Industrial Economics and Strategy/Aalborg University, Department of Business Studies.
  8. Karolina Safarzyńska & Jeroen Bergh, 2010. "Evolutionary models in economics: a survey of methods and building blocks," Journal of Evolutionary Economics, Springer, vol. 20(3), pages 329-373, June.
  9. Patalano, Roberta, 2007. "Resistance to change. Exploring the convergence of institutions, organizations and the mind toward a common phenomenon," MPRA Paper 3342, University Library of Munich, Germany.
  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).

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