Maintaining Population Diversity in Evolutionary Art

  • E. den Heijer
  • A. E. Eiben
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7247)


Evolutionary art is inherently more concerned with exploration than with exploitation, because users are typically more interested in evolving a collection of diverse images than converging to a single ‘optimal’ image. However, maintaining diversity is a difficult task. In this paper we investigate various techniques to promote population diversity in evolutionary art. We introduce customised mutation and crossover operators that perform a local search to diversify individuals and evaluate the effect of these operators on population diversity. We also investigate alternatives for the fitness crowding operator in NSGA-II; we use a genotype and a phenotype distance function to calculate the crowding distance and investigate their effect on population diversity.


Local Search Distance Function Genetic Program Pareto Front Population Diversity 
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 2012

Authors and Affiliations

  • E. den Heijer
    • 1
    • 2
  • A. E. Eiben
    • 2
  1. 1.Objectivation B.V.AmsterdamThe Netherlands
  2. 2.Vrije UniversiteitAmsterdamThe Netherlands

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