Fractional Genetic Programming with Probability Density Data

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

@InProceedings{conf/csp/Rataj14,

• author = "Artur Rataj",
• title = "Fractional Genetic Programming with Probability Density Data",
• booktitle = "Proceedings of the 23th International Workshop on Concurrency, Specification and Programming, Chemnitz, Germany, September 29 - October 1, 2014",
• publisher = "CEUR-WS.org",
• year = "2014",
• volume = "1269",
• editor = "Louchka Popova-Zeugmann",
• pages = "220--231",
• series = "CEUR Workshop Proceedings",
• keywords = "genetic algorithms, genetic programming, real-coded genetic algorithm, evolutionary method, probability density",
• bibdate = "2014-10-27",
• bibsource = "DBLP, http://dblp.uni-trier.de/db/conf/csp/csp2014.html#Rataj14",
• URL = "http://ceur-ws.org/Vol-1269",
• URL = "http://ceur-ws.org/Vol-1269/paper220.pdf",
• size = "12 pages",
• abstract = "We extend the fractional genetic programming scheme with data elements that are no more scalar, but instead are similar to probability density functions. The extension straightforwardly fits into fractional programming, in which data elements are blended from several values. In the case of our previous work, the blend produced a single scalar value. The extension proposes to build an approximate probability density function out of the blended elements. The extension turned out to be very effective in an unsuspected way: when a data element, despite being destined to approximate a probability density, represented a single-dimensional image of spatial data.",

}

Genetic Programming entries for Artur Rataj

Citations