Fitness and novelty in evolutionary art

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Authors

  • Adriano Vinhas
  • Filipe Assuncção
  • João Correira
  • Aniko Ekárt
  • Penousal Machado

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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.

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Publication date17 Mar 2016
Publication titleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsColin Johnson, Vic Ciesielski, João Correia, Penousal Machado
PublisherSpringer
Pages225-240
Number of pages16
ISBN (Electronic)978-3-319-31008-4
ISBN (Print)978-3-319-31007-7
Original languageEnglish
Event5th International Conference on Evolutionary and Biologically Inspired Music, Sound, Art and design - Porto, Portugal
Duration: 30 Mar 20161 Apr 2016

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume9596
ISSN (Print)0302-9743

Conference

Conference5th International Conference on Evolutionary and Biologically Inspired Music, Sound, Art and design
Abbreviated titleEvoMUSART 2016
CountryPortugal
CityPorto
Period30/03/161/04/16

    Keywords

  • novelty search, evolutionary, art, multi-objective optimisation

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