Fitness and novelty in evolutionary art

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.
LanguageEnglish
Title of host publicationLecture 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
DOIs
Publication statusPublished - 17 Mar 2016
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

Fingerprint

Fitness
Engines
Engine
Multiobjective optimization
Multiobjective Optimization Problems
Grammar
Large Set
Metric
Demonstrate
Art
Context
Design
Object

Keywords

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

Cite this

Vinhas, A., Assuncção, F., Correira, J., Ekárt, A., & Machado, P. (2016). Fitness and novelty in evolutionary art. In C. Johnson, V. Ciesielski, J. Correia, & P. Machado (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 225-240). (Lecture Notes in Computer Science; Vol. 9596). Springer. https://doi.org/10.1007/978-3-319-31008-4_16
Vinhas, Adriano ; Assuncção, Filipe ; Correira, João ; Ekárt, Aniko ; Machado, Penousal. / Fitness and novelty in evolutionary art. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). editor / Colin Johnson ; Vic Ciesielski ; João Correia ; Penousal Machado. Springer, 2016. pp. 225-240 (Lecture Notes in Computer Science).
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Vinhas, A, Assuncção, F, Correira, J, Ekárt, A & Machado, P 2016, Fitness and novelty in evolutionary art. in C Johnson, V Ciesielski, J Correia & P Machado (eds), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Lecture Notes in Computer Science, vol. 9596, Springer, pp. 225-240, 5th International Conference on Evolutionary and Biologically Inspired Music, Sound, Art and design, Porto, Portugal, 30/03/16. https://doi.org/10.1007/978-3-319-31008-4_16

Fitness and novelty in evolutionary art. / Vinhas, Adriano; Assuncção, Filipe; Correira, João; Ekárt, Aniko; Machado, Penousal.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). ed. / Colin Johnson; Vic Ciesielski; João Correia; Penousal Machado. Springer, 2016. p. 225-240 (Lecture Notes in Computer Science; Vol. 9596).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Vinhas A, Assuncção F, Correira J, Ekárt A, Machado P. Fitness and novelty in evolutionary art. In Johnson C, Ciesielski V, Correia J, Machado P, editors, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer. 2016. p. 225-240. (Lecture Notes in Computer Science). https://doi.org/10.1007/978-3-319-31008-4_16