Matrix Analysis of Genetic Programming Mutation

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

@InProceedings{parkes:2012:EuroGP,
  author =       "Andrew J. Parkes and Ender Ozcan and Matthew R. Hyde",
  title =        "Matrix Analysis of Genetic Programming Mutation",
  booktitle =    "Proceedings of the 15th European Conference on Genetic
                 Programming, EuroGP 2012",
  year =         "2012",
  month =        "11-13 " # apr,
  editor =       "Alberto Moraglio and Sara Silva and 
                 Krzysztof Krawiec and Penousal Machado and Carlos Cotta",
  series =       "LNCS",
  volume =       "7244",
  publisher =    "Springer Verlag",
  address =      "Malaga, Spain",
  pages =        "158--169",
  organisation = "EvoStar",
  isbn13 =       "978-3-642-29138-8",
  DOI =          "doi:10.1007/978-3-642-29139-5_14",
  size =         "12 pages",
  keywords =     "genetic algorithms, genetic programming,
                 Genotype-phenotype mapping",
  abstract =     "Heuristic policies for combinatorial optimisation
                 problems can be found by using Genetic programming (GP)
                 to evolve a mathematical function over variables given
                 by the current state of the problem, and whose value is
                 used to determine action choices (such as preferred
                 assignments or branches). If all variables have finite
                 discrete domains, then the expressions can be converted
                 to an equivalent lookup table or `decision matrix'.
                 Spaces of such matrices often have natural distance
                 metrics (after conversion to a standard form). As a
                 case study, and to support the understanding of GP as a
                 meta-heuristic, we extend previous bin-packing work and
                 compare the distances between matrices from before and
                 after a GP-driven mutation. We find that GP mutations
                 often correspond to large moves within the space of
                 decision matrices. This strengthens evidence that the
                 role of mutations within GP might be somewhat different
                 than their role within Genetic Algorithms.",
  notes =        "Automated development of heuristics for the bin
                 packing problem. Hyper-heuristics. ECJ. Part of
                 \cite{Moraglio:2012:GP} EuroGP'2012 held in conjunction
                 with EvoCOP2012 EvoBIO2012, EvoMusArt2012 and
                 EvoApplications2012",
}

Genetic Programming entries for Andrew J Parkes Ender Ozcan Matthew R Hyde

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