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Simulations with Genetic Algorithms in Economic Systems

  • Herbert Dawid
Part of the Lecture Notes in Economics and Mathematical Systems book series (LNE, volume 441)

Abstract

In chapter 5 we presented some simulations of genetic learning in evolutionary games. As it is, evolutionary games are however always a stylized model of an economic system, since no explicit structure of the model is given, but only the payoffs of the different actions in different circumstances. In chapter 3 we argued that economic systems are SDF systems because all the single individuals together determine the state of the economy, which again determines the payoffs of the different actions of the individuals. If we consider evolutionary games we always assume that the payoff of any action is the average of the payoffs which would be attained against all the different individuals (or more accurately against a uniform population acting like this individual) in the population. In other words, if we consider genetic learning in evolutionary games the fitness function is always a linear function of the state of the population. Obviously there are however many economic models where no such linear relationship exists and these differ in the basic structure from evolutionary games.

Keywords

Genetic Algorithm Economic System Equilibrium Price Rational Expectation Binary String 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1996

Authors and Affiliations

  • Herbert Dawid
    • 1
  1. 1.Institute of Management ScienceUniversity of ViennaViennaAustria

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