Comparing the Performance of the Evolvable PiGrammatical Evolution Genotype-Phenotype Map to Grammatical Evolution in the Dynamic Ms. Pac-Man Environment

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

@InProceedings{galvan-lopez_etal:cec2010,
  author =       "Edgar Galvan-Lopez and David Fagan and Eoin Murphy and 
                 John Mark Swafford and Alexandros Agapitos and 
                 Michael O'Neill and Anthony Brabazon",
  title =        "Comparing the Performance of the Evolvable
                 {PiGrammatical} Evolution Genotype-Phenotype Map to
                 Grammatical Evolution in the Dynamic {Ms. Pac-Man}
                 Environment",
  booktitle =    "2010 IEEE World Congress on Computational
                 Intelligence",
  pages =        "1587--1594",
  year =         "2010",
  address =      "Barcelona, Spain",
  month =        "18-23 " # jul,
  organization = "IEEE Computational Intelligence Society",
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming, grammatical
                 evolution",
  isbn13 =       "978-1-4244-6910-9",
  DOI =          "doi:10.1109/CEC.2010.5586508",
  abstract =     "In this work, we examine the capabilities of two forms
                 of mappings by means of Grammatical Evolution (GE) to
                 successfully generate controllers by combining
                 high-level functions in a dynamic environment. In this
                 work we adopted the Ms. Pac-Man game as a benchmark
                 test bed. We show that the standard GE mapping and
                 Position Independent GE (piGE) mapping achieve similar
                 performance in terms of maximising the score. We also
                 show that the controllers produced by both approaches
                 have an overall better performance in terms of
                 maximising the score compared to a hand-coded agent.
                 There are, however, significant differences in the
                 controllers produced by these two approaches: standard
                 GE produces more controllers with invalid code, whereas
                 the opposite is seen with piGE.",
  notes =        "WCCI 2010. Also known as \cite{5586508}",
}

Genetic Programming entries for Edgar Galvan Lopez David Fagan Eoin Murphy John Mark Swafford Alexandros Agapitos Michael O'Neill Anthony Brabazon

Citations