Promoting Phenotypic Diversity in Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{Jackson:2010:PPSN,
  author =       "David Jackson",
  title =        "Promoting Phenotypic Diversity in Genetic
                 Programming",
  booktitle =    "PPSN 2010 11th International Conference on Parallel
                 Problem Solving From Nature",
  year =         "2010",
  editor =       "Robert Schaefer and Carlos Cotta and 
                 Joanna Kolodziej and Guenter Rudolph",
  publisher =    "Springer",
  pages =        "472--481",
  series =       "Lecture Notes in Computer Science",
  address =      "Krakow, Poland",
  month =        "11-15 " # sep,
  volume =       "6239",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1007/978-3-642-15871-1_48",
  abstract =     "Population diversity is generally seen as playing a
                 crucial role in the ability of evolutionary computation
                 techniques to discover solutions. In genetic
                 programming, diversity metrics are usually based on
                 structural properties of individual program trees, but
                 are also sometimes based on the spread of fitness
                 values in the population. We explore the use of a
                 further interpretation of diversity, in which
                 differences are measured in terms of the behaviour of
                 programs when executed. Although earlier work has shown
                 that improving behavioural diversity in initial GP
                 populations can have a marked beneficial effect on
                 performance, further analysis reveals that lack of
                 behavioural diversity is a problem throughout whole
                 runs, even when other diversity levels are high. To
                 address this, we enhance phenotypic diversity via
                 modifications to the crossover operator, and show that
                 this can lead to additional performance improvements.",
  affiliation =  "Dept. of Computer Science, University of Liverpool,
                 Liverpool, L69 3BX United Kingdom",
}

Genetic Programming entries for David Jackson

Citations