Addressing the Even-n-parity problem using Compressed Linear Genetic Programming

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

@InProceedings{Parent:gecco05lbp,
  author =       "Johan Parent and Annie Nowe and Anne Defaweux",
  title =        "Addressing the Even-n-parity problem using Compressed
                 Linear Genetic Programming",
  booktitle =    "Late breaking paper at Genetic and Evolutionary
                 Computation Conference {(GECCO'2005)}",
  year =         "2005",
  month =        "25-29 " # jun,
  editor =       "Franz Rothlauf",
  address =      "Washington, D.C., USA",
  URL =          "http://www.cs.bham.ac.uk/~wbl/biblio/gecco2005lbp/papers/54-parent.pdf",
  keywords =     "genetic algorithms, genetic programming, modules,
                 modularisation, building blocks",
  abstract =     "Compressed Linear Genetic Programming (cl-GP) uses
                 substring compression as a modularisation scheme.
                 Despite the fact that the compression of substrings
                 assumes a tight linkage between alleles, this approach
                 improves the GP search process. The compression of the
                 genotype, which is a form of linkage learning, provides
                 both a protection mechanism and a form of genetic code
                 reuse. This text presents the results obtained with the
                 cl-GP on the Even-n-parity problem. Results indicate
                 that the modularization of the cl-GP performs better
                 than a normal l-GP as it allows the cl-GP to preserve
                 useful gene combinations. Additionally the cl-GP
                 modularisation is well suited for problems where the
                 problem size is adjusted in a co-evolutionary setup,
                 the problem size increases each time a solution is
                 found",
  notes =        "Distributed on CD-ROM at GECCO-2005

                 Pairs of adjacent functions and/or terminals present in
                 large numbers in 10 fit programs may be replaced by a
                 single symbol before crossover and mutation. The
                 intention being to keep them together as a building
                 block.

                 Representation is a linearised (depth first) tree. Non
                 standard meaning given to {"}co-evolutionary{"}.

                 Up to even-10-parity evolved (cf \cite{poli:1999:22par}
                 22 parity). Tight limit on program size. NOOP.
                 Elitism.

                 Why does size of dictionary rise after generation
                 zero?",
}

Genetic Programming entries for Johan Parent Ann Nowe Anne Defaweux

Citations