- author = "Alan Blair",
- title = "Adversarial Evolution and Deep Learning - How Does an Artist Play with Our Visual System?",
- booktitle = "8th International Conference on Computational Intelligence in Music, Sound, Art and Design, EvoMusArt 2019",
- year = "2019",
- editor = "Aniko Ekart and Antonios Liapis and Luz Castro",
- series = "LNCS",
- volume = "11453",
- publisher = "Springer",
- pages = "18--34",
- address = "Leipzig, Germany",
- month = "24-26 " # apr,
- organisation = "Species",
- keywords = "genetic algorithms, genetic programming, ANN, Evolutionary art, ai-generated art, Artist-critic coevolution, Adversarial training, Computational creativity",
- isbn13 = "978-3-030-16666-3",
-
DOI = "
doi:10.1007/978-3-030-16667-0_2",
- abstract = "We create artworks using adversarial coevolution between a genetic program (hercl) generator and a deep convolutional neural network (LeNet) critic. The resulting artificially intelligent artist, whimsically named Hercule LeNet, aims to produce images of low algorithmic complexity which nevertheless resemble a set of real photographs well enough to fool an adversarially trained deep learning critic modelled on the human visual system. Although it is not exposed to any pre-existing art, or asked to mimic the style of any human artist, nevertheless it discovers for itself many of the stylistic features associated with influential art movements of the 19th and 20th Century. A detailed analysis of its work can help us to better understand the way an artist plays with the human visual system to produce aesthetically appealing images.",
-
notes = "Cover SIGEvolution 12(2)
\cite{Ochoa:2019:sigevolution}.
EvoMusArt2019 held in conjunction with EuroGP'2019 EvoCOP2019 and EvoApplications2019 http://www.evostar.org/2019/cfp_evomusart.php",
