Fractional Genetic Programming with Probability Density Data

Created by W.Langdon from gp-bibliography.bib Revision:1.4504

  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 =    "",
  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
  bibdate =      "2014-10-27",
  bibsource =    "DBLP,
  URL =          "",
  URL =          "",
  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