Graph-Based Evolutionary Art

  • Penousal Machado
  • João Correia
  • Filipe Assunção


A graph-based approach for the evolution of Context Free Design Grammars is presented. Each genotype is a directed hierarchical graph and, as such, the evolutionary engine employs graph-based crossover and mutation. We introduce six different fitness functions based on evolutionary art literature and conduct a wide set of experiments. We begin by assessing the adequacy of the system and establishing the experimental parameters. Afterwards, we conduct evolutionary runs using each fitness function individually. Finally, experiments where a combination of these functions is used to assign fitness are performed. Overall, the experimental results show the ability of the system to optimize the considered functions, individually and combined, and to evolve images that have the desired visual characteristics.


Fractal Dimension Fitness Function Production Rule Evolutionary Engine Scalable Vector Graphic 
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.



This research is partially funded by: Fundação para a Ciência e Tecnologia (FCT), Portugal, under the grant SFRH/BD/90968/2012; project ConCreTe. The project ConCreTe acknowledges the financial support of the Future and Emerging Technologies (FET) programme within the Seventh Framework Programme for Research of the European Commission, under FET grant number 611733. We acknowledge and thank the contribution of Manuel Levi who implemented the Contrasting Colors fitness function.

Supplementary material

327421_1_En_1_MOESM1_ESM.xlsx (642 kb)
graph (xlsx 642 kb)


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Penousal Machado
    • 1
  • João Correia
    • 1
  • Filipe Assunção
    • 1
  1. 1.CISUC, Department of Informatics EngineeringUniversity of CoimbraCoimbraPortugal

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