Fitness and Novelty in Evolutionary Art

  • Adriano Vinhas
  • Filipe Assunção
  • João Correia
  • Aniko Ekárt
  • Penousal Machado
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9596)

Abstract

In this paper the effects of introducing novelty search in evolutionary art are explored. Our algorithm combines fitness and novelty metrics to frame image evolution as a multi-objective optimisation problem, promoting the creation of images that are both suitable and diverse. The method is illustrated by using two evolutionary art engines for the evolution of figurative objects and context free design grammars. The results demonstrate the ability of the algorithm to obtain a larger set of fit images compared to traditional fitness-based evolution, regardless of the engine used.

Keywords

Novelty search Evolutionary art Multi-objective optimisation 

Notes

Acknowledgments

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. This research is also partially funded by: Fundação para a Ciência e Tecnologia (FCT), Portugal, under the grant SFRH/BD/90968/2012. The authors also acknowledge the feedback provided by the blind reviewers of this paper.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Adriano Vinhas
    • 1
  • Filipe Assunção
    • 1
  • João Correia
    • 1
  • Aniko Ekárt
    • 2
  • Penousal Machado
    • 1
  1. 1.Department of Informatics Engineering, CISUCUniversity of CoimbraCoimbraPortugal
  2. 2.Aston Lab for Intelligent Collectives Engineering (ALICE), Computer ScienceAston UniversityBirminghamUK

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