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

  • Giovanni Dosi
  • Luigi Marengo
  • Andrea Bassanini
  • Marco Valente
Conference paper

DOI: 10.1007/978-3-642-57646-1_2

Cite this paper as:
Dosi G., Marengo L., Bassanini A., Valente M. (2002) Norms as emergent properties of adaptive learning: The case of economic routines. In: Cantner U., Hanusch H., Klepper S. (eds) Economic Evolution, Learning, and Complexity. Physica, Heidelberg

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.

Key words

Computability Genetic Programming Oligopoly 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Giovanni Dosi
    • 1
    • 2
  • Luigi Marengo
    • 3
  • Andrea Bassanini
    • 4
  • Marco Valente
    • 5
  1. 1.Scvola Superiore S. AnnaPisaItaly
  2. 2.IIASALaxenburgAustria
  3. 3.Department of EconomicsUniversity of TrentoTrentoItaly
  4. 4.Faculty of StatisticsUniversity “La Sapienza” OECDRome ParisFrance
  5. 5.Aalborg UniversityAalborgDenmark

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