Empirical Comparison of Evolutionary Representations of the Inverse Problem for Iterated Function Systems

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{eurogp07:sarafopoulos,

• author = "Anargyros Sarafopoulos and Bernard Buxton",
• title = "Empirical Comparison of Evolutionary Representations of the Inverse Problem for Iterated Function Systems",
• editor = "Marc Ebner and Michael O'Neill and Anik\'o Ek\'art and Leonardo Vanneschi and Anna Isabel Esparcia-Alc\'azar",
• booktitle = "Proceedings of the 10th European Conference on Genetic Programming",
• publisher = "Springer",
• series = "Lecture Notes in Computer Science",
• volume = "4445",
• year = "2007",
• address = "Valencia, Spain",
• month = "11-13 " # apr,
• pages = "68--77",
• organisation = "EvoStar",
• keywords = "genetic algorithms, genetic programming",
• ISBN = "3-540-71602-5",
• isbn13 = "978-3-540-71602-0",
• DOI = "doi:10.1007/978-3-540-71605-1_7",
• size = "10 pages",
• abstract = "In this paper we present an empirical comparison between evolutionary representations for the resolution of the inverse problem for iterated function systems (IFS). We introduce a class of problem instances that can be used for the comparison of the inverse IFS problem as well as a novel technique that aids exploratory analysis of experiment data. Our comparison suggests that representations that exploit problem specific information, apart from quality/fitness feedback, perform better for the resolution of the inverse problem for IFS.",
• notes = "Part of \cite{ebner:2007:GP} EuroGP'2007 held in conjunction with EvoCOP2007, EvoBIO2007 and EvoWorkshops2007",

}

Genetic Programming entries for Anargyros Sarafopoulos Bernard Buxton

Citations