Automated Aesthetic Selection of Evolutionary Art by Distance Based Classification of Genomes and Phenomes using the Universal Similarity Metric
Created by W.Langdon from
gp-bibliography.bib Revision:1.8129
- @InProceedings{svangard:evows04,
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author = "Nils Svangard and Peter Nordin",
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title = "Automated Aesthetic Selection of Evolutionary Art by
Distance Based Classification of Genomes and Phenomes
using the Universal Similarity Metric",
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booktitle = "Applications of Evolutionary Computing,
EvoWorkshops2004: {EvoBIO}, {EvoCOMNET}, {EvoHOT},
{EvoIASP}, {EvoMUSART}, {EvoSTOC}",
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year = "2004",
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month = "5-7 " # apr,
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editor = "Guenther R. Raidl and Stefano Cagnoni and
Jurgen Branke and David W. Corne and Rolf Drechsler and
Yaochu Jin and Colin R. Johnson and Penousal Machado and
Elena Marchiori and Franz Rothlauf and George D. Smith and
Giovanni Squillero",
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series = "LNCS",
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volume = "3005",
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address = "Coimbra, Portugal",
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publisher = "Springer Verlag",
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publisher_address = "Berlin",
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pages = "447--456",
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keywords = "genetic algorithms, genetic programming, evolutionary
computation",
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ISBN = "3-540-21378-3",
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DOI = "doi:10.1007/978-3-540-24653-4_46",
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abstract = "In this paper we present a new technique for
automatically approximating the aesthetic fitness of
evolutionary art. Instead of assigning fitness values
to images interactively, we use the Universal
Similarity Metric to predict how interesting new images
are to the observer based on a library of aesthetic
images. In order to approximate the Information
Distance, and find the images most similar to the
training set, we use a combination of zip-compression,
for genomes, and jpeg-compression of the final images.
We evaluated the prediction accuracy of our system by
letting the user label a new set of images and then
compare that to what our system classifies as the most
aesthetically pleasing images. Our experiments indicate
that the Universal Similarity Metric can successfully
be used to classify what images and genomes are
aesthetically pleasing, and that it can clearly
distinguish between 'ugly' and 'pretty' images with an
accuracy better than the random baseline.",
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notes = "EvoWorkshops2004",
- }
Genetic Programming entries for
Nils Svangard
Peter Nordin
Citations