Tree-Adjunct Grammatical Evolution

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "Eoin Murphy and Michael O'Neill and 
                 Edgar Galvan-Lopez and Anthony Brabazon",
  title =        "Tree-Adjunct Grammatical Evolution",
  booktitle =    "2010 IEEE World Congress on Computational
  pages =        "4449--4456",
  year =         "2010",
  address =      "Barcelona, Spain",
  month =        "18-23 " # jul,
  organization = "IEEE Computational Intelligence Society",
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming, grammatical
                 evolution, TAG",
  isbn13 =       "978-1-4244-6910-9",
  DOI =          "doi:10.1109/CEC.2010.5586497",
  size =         "8 pages",
  abstract =     "In this paper we investigate the application of
                 tree-adjunct grammars to grammatical evolution. The
                 standard type of grammar used by grammatical evolution,
                 context-free grammars, produce a subset of the
                 languages that tree-adjunct grammars can produce,
                 making tree-adjunct grammars, expressively, more
                 powerful. In this study we shed some light on the
                 effects of tree-adjunct grammars on grammatical
                 evolution, or tree-adjunct grammatical evolution. We
                 perform an analytic comparison of the performance of
                 both setups, i.e., grammatical evolution and
                 tree-adjunct grammatical evolution, across a number of
                 classic genetic programming benchmarking problems. The
                 results firmly indicate that tree-adjunct grammatical
                 evolution has a better overall performance (measured in
                 terms of finding the global optima).",
  notes =        "adjunction is the only composition operator, TAG3P
                 alpha trees. Auxiliary trees= beta trees. Elementary
                 trees. TAGE (fixed chromosome length). GEVA v1.1.
                 Even-5-parity, Santa Fe Ant, symbolic regression,
                 6-Mux, Max problem \cite{Gathercole:1996:aicrtd}
                 \cite{langdon:1997:MAX}. WCCI 2010. Also known as

Genetic Programming entries for Eoin Murphy Michael O'Neill Edgar Galvan Lopez Anthony Brabazon