Investigating Aesthetic Features to Model Human Preference in Evolutionary Art

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Li:2012:EvoMUSART,

• author = "Yang Li and Changjun Hu and Ming Chen and Jingyuan Hu",
• title = "Investigating Aesthetic Features to Model Human Preference in Evolutionary Art",
• booktitle = "Proceedings of the 1st International Conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design, EvoMUSART 2012",
• year = "2012",
• month = "11-13 " # apr,
• editor = "Penousal Machado and Juan Romero and Adrian Carballal",
• series = "LNCS",
• volume = "7247",
• publisher = "Springer Verlag",
• address = "Malaga, Spain",
• pages = "153--164",
• organisation = "EvoStar",
• keywords = "genetic algorithms, genetic programming, Aesthetic learning, evolutionary art, interactive evolutionary computation, computational aesthetics",
• isbn13 = "978-3-642-29141-8",
• DOI = "doi:10.1007/978-3-642-29142-5_14",
• abstract = "In this paper we investigate aesthetic features in learning aesthetic judgements in an evolutionary art system. We evolve genetic art with our evolutionary art system, BioEAS, by using genetic programming and an aesthetic learning model. The model is built by learning both phenotype and genotype features, which we extracted from internal evolutionary images and external real world paintings, which could lead to more interesting paths. By learning aesthetic judgment and applying the knowledge to evolve aesthetical images, the model helps user to automate the process of evolutionary process. Several independent experimental results show that our system is efficient to reduce user fatigue in evolving art.",
• notes = "Part of \cite{Machado:2012:EvoMusArt_proc} EvoMUSART'2012 held in conjunction with EuroGP2012, EvoCOP2012, EvoBIO2012 and EvoApplications2012",

}

Genetic Programming entries for Yang Li Changjun Hu Ming Chen Jingyuan Hu

Citations