Inductive inference of chaotic series by Genetic Programming: a Solomonoff-based approach

Created by W.Langdon from gp-bibliography.bib Revision:1.8081

@InProceedings{conf/sac/FalcoTCP05,

• title = "Inductive inference of chaotic series by Genetic Programming: a Solomonoff-based approach",
• author = "Ivan {De Falco} and Ernesto Tarantino and Antonio {Della Cioppa} and A. Passaro",
• year = "2005",
• pages = "957--958",
• editor = "Hisham Haddad and Lorie M. Liebrock and Andrea Omicini and Roger L. Wainwright",
• booktitle = "Proceedings of the 2005 ACM Symposium on Applied Computing (SAC)",
• publisher = "ACM",
• address = "Santa Fe, New Mexico, USA",
• month = mar # " 13-17",
• organisation = "ACM",
• bibdate = "2006-02-10",
• bibsource = "DBLP, http://dblp.uni-trier.de/db/conf/sac/sac2005.html#FalcoTCP05",
• keywords = "genetic algorithms, genetic programming, Automatic Programming, Algorithms, Experimentation, Inductive inference, Chaotic series",
• ISBN = "1-58113-964-0",
• DOI = "doi:10.1145/1066677.1066897",
• size = "2 pages",
• abstract = "A Genetic Programming approach to inductive inference of chaotic series, with reference to Solomonoff complexity, is presented. It consists in evolving a population of mathematical expressions looking for the 'optimal' one that generates a given chaotic data series. Validation is performed on the Logistic, the Henon and the Mackey-Glass series. The method is shown effective in obtaining the analytical expression of the first two series, and in achieving very good results on the third one.",

}

Genetic Programming entries for Ivanoe De Falco Ernesto Tarantino Antonio Della Cioppa A Passaro

Citations