Grammatical Bias and Building Blocks in Meta-Grammar Grammatical Evolution

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

  author =       "Erik Hemberg and Michael O'Neill and 
                 Anthony Brabazon",
  title =        "Grammatical Bias and Building Blocks in Meta-Grammar
                 Grammatical Evolution",
  booktitle =    "2008 IEEE World Congress on Computational
  year =         "2008",
  editor =       "Jun Wang",
  pages =        "3775--3782",
  address =      "Hong Kong",
  month =        "1-6 " # jun,
  organization = "IEEE Computational Intelligence Society",
  publisher =    "IEEE Press",
  isbn13 =       "978-1-4244-1823-7",
  file =         "EC0802.pdf",
  DOI =          "doi:10.1109/CEC.2008.4631309",
  abstract =     "This paper describes and tests the utility of a meta
                 Grammar approach to Grammatical Evolution (GE). Rather
                 than employing a fixed grammar as is the case with
                 canonical GE, under a meta Grammar approach the grammar
                 that is used to specify the construction of a
                 syntactically correct solution is itself allowed to
                 evolve. The ability to evolve a grammar in the context
                 of GE means that useful bias towards specific
                 structures and solutions can be evolved and directly
                 incorporated into the grammar during a run. This
                 approach facilitates the evolution of modularity and
                 reuse both on structural and symbol levels and
                 consequently could enhance both the scalability of GE
                 and its adaptive potential in dynamic environments. In
                 this paper an analysis of the extent that building
                 block structures created in the grammars are used in
                 the solution is undertaken. It is demonstrated that
                 building block structures are incorporated into the
                 evolving grammars and solutions at a rate higher than
                 would be expected by random search. Furthermore, the
                 results indicate that grammar design can be an
                 important factor in performance.",
  keywords =     "genetic algorithms, genetic programming, grammatical
  notes =        "WCCI 2008 - A joint meeting of the IEEE, the INNS, the
                 EPS and the IET.",

Genetic Programming entries for Erik Hemberg Michael O'Neill Anthony Brabazon