On Two Types of GA-Learning

  • Nicolaas J. Vriend
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 100)


We distinguish two types of learning with a Genetic Algorithm. A population learning Genetic Algorithm (or pure GA), and an individual learning Genetic Algorithm (basically a GA combined with a Classifier System ). The difference between these two types of GA is often neglected, but we show that for a broad class of problems this difference is essential as it may lead to widely differing performances. The underlying cause for this is a so called spite effect.


Nash Equilibrium Output Level Inverse Demand Function Walrasian Equilibrium Output Rule 
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 2002

Authors and Affiliations

  • Nicolaas J. Vriend
    • 1
  1. 1.Queen Mary, University of LondonUK

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