Artificial evolution for computer graphics
Proceedings of the 18th annual conference on Computer graphics and interactive techniques
Creative evolutionary systems
Eons of genetically evolved algorithmic images
Creative evolutionary systems
Procedural texture evolution using multi-objective optimization
New Generation Computing
The Art of Artificial Evolution: A Handbook on Evolutionary Art and Music (Natural Computing Series)
The Art of Artificial Evolution: A Handbook on Evolutionary Art and Music (Natural Computing Series)
Open problems in evolutionary music and art
EC'05 Proceedings of the 3rd European conference on Applications of Evolutionary Computing
Comparing aesthetic measures for evolutionary art
EvoCOMNET'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part II
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Computational Aesthetics'05 Proceedings of the First Eurographics conference on Computational Aesthetics in Graphics, Visualization and Imaging
Global contrast factor - a new approach to image contrast
Computational Aesthetics'05 Proceedings of the First Eurographics conference on Computational Aesthetics in Graphics, Visualization and Imaging
Benford's law for natural and synthetic images
Computational Aesthetics'05 Proceedings of the First Eurographics conference on Computational Aesthetics in Graphics, Visualization and Imaging
Evolving art with scalable vector graphics
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Maintaining population diversity in evolutionary art
EvoMUSART'12 Proceedings of the First international conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design
Investigating aesthetic features to model human preference in evolutionary art
EvoMUSART'12 Proceedings of the First international conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design
Learning aesthetic judgements in evolutionary art systems
Genetic Programming and Evolvable Machines
| Hi-index | 0.00 |
In this paper we investigate the applicability of Multi-Objective Optimization (MOO) in Evolutionary Art. We evolve images using an unsupervised evolutionary algorithm and we use two aesthetic measures as fitness functions concurrently. We use three different pairs from a set of three aesthetic measures and we compare the output of each pair to the output of other pairs, and to the output of experiments with a single aesthetic measure (non-MOO). We investigate 1) whether properties of aesthetic measures can be combined using MOO and 2) whether the use of MOO in evolutionary art results in different images, or perhaps "better" images. All images in this paper can be viewed in colour at http://www.few.vu.nl/~eelco/