Towards identifying salient patterns in genetic programming individuals

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@PhdThesis{a.m.joo.phd.069952236,
  author =       "Andras Matyas Joo",
  title =        "Towards identifying salient patterns in genetic
                 programming individuals",
  school =       "Aston University",
  year =         "2010",
  address =      "Birmingham, UK",
  month =        jun,
  keywords =     "genetic algorithms, genetic programming, tree mining,
                 data mining, PGA",
  URL =          "http://eprints.aston.ac.uk/13364/",
  URL =          "http://eprints.aston.ac.uk/13364/1/a.m.joo.phd.069952236.pdf",
  URL =          "http://ethos.bl.uk/OrderDetails.do?did=29&uin=uk.bl.ethos.533151",
  size =         "90 pages",
  abstract =     "This thesis addresses the problem of offline
                 identification of salient patterns in genetic
                 programming individuals. It discusses the main issues
                 related to automatic pattern identification systems,
                 namely that these (a) should help in understanding the
                 final solutions of the evolutionary run, (b) should
                 give insight into the course of evolution and (c)
                 should be helpful in optimising future runs. Moreover,
                 it proposes an algorithm, Extended Pattern Growing
                 Algorithm ([E]PGA) to extract, filter and sort the
                 identified patterns so that these fulfill as many as
                 possible of the following criteria: (a) they are
                 representative for the evolutionary run and/or search
                 space, (b) they are human-friendly and (c) their
                 numbers are within reasonable limits. The results are
                 demonstrated on six problems from different domains",
  notes =        "[E]PGA

                 uk.bl.ethos.533151",
}

Genetic Programming entries for Andras Joo

Citations