Mixed IFS: Resolution of the Inverse Problem Using Genetic Programming

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

@InCollection{Cretin:al:EA95,

• author = "Guillaume Cretin and Evelyne Lutton and Jacques Levy-Vehel and Philippe Glevarec and Cedric Roll",
• title = "Mixed {IFS}: Resolution of the Inverse Problem Using Genetic Programming",
• booktitle = "Artificial Evolution",
• publisher = "Springer Verlag",
• year = "1996",
• editor = "Jean-Marc Alliot and Evelyne Lutton and Edmund Ronald and Marc Schoenauer and Dominique Snyers",
• volume = "1063",
• series = "LNCS",
• pages = "247--258",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-3-540-61108-0",
• DOI = "doi:10.1007/3-540-61108-8_42",
• size = "11 pages",
• abstract = "We address here the resolution of the so-called inverse problem for IFS. This problem has already been widely considered, and some studies have been performed for affine IFS, using deterministic or stochastic methods (simulated annealing or Genetic Algorithm) [9, 12, 6]. When dealing with non affine IFS, the usual techniques do not perform well, except if some a priori hypotheses on the structure of IFS (number and type functions) are made. A Genetic Programming method is investigated to solve the general inverse problem, which permits to perform at the same time a numeric and a symbolic optimisation. The use of mixed IFS, as we call them, may enlarge the scope of some applications, as for example image compression, because they allow to code a wider range of shapes.",
• notes = "Selected papers from two conferences: Evolution Artificielle 94 and Evolution Artificielle 95 http://www.cmap.polytechnique.fr/www.eark/ea95.html see also \cite{lutton:1995:IFScs} and \cite{lutton:1995:IFScs}",
• affiliation = "INRIA-Rocquencourt B.P. 105 78153 Le Chesnay Cedex France B.P. 105 78153 Le Chesnay Cedex France",

}

Genetic Programming entries for Guillaume Cretin Evelyne Lutton Jacques Levy-Vehel Philippe Glevarec Cedric Roll

Citations