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

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@Article{dosi:1999:nepal:er,
  author =       "Giovanni Dosi and Luigi Marengo and 
                 Andrea Bassanini and Marco Valente",
  title =        "Norms as emergent properties of adaptive learning: The
                 case of economic routines",
  journal =      "Journal of Evolutionary Economics",
  year =         "1999",
  volume =       "9",
  number =       "1",
  pages =        "5--26",
  keywords =     "genetic algorithms, genetic programming,
                 computability, oligopoly",
  ISSN =         "0936-9937",
  DOI =          "doi:10.1007/s001910050073",
  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.",
}

Genetic Programming entries for Giovanni Dosi Luigi Marengo Andrea Bassanini Marco Valente

Citations