Automatically Designing More General Mutation Operators of Evolutionary Programming for Groups of Function Classes Using a Hyper-Heuristic

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

@InProceedings{Hong:2016:GECCO,
  author =       "Libin Hong",
  title =        "Automatically Designing More General Mutation
                 Operators of Evolutionary Programming for Groups of
                 Function Classes Using a Hyper-Heuristic",
  booktitle =    "GECCO '16: Proceedings of the 2016 Annual Conference
                 on Genetic and Evolutionary Computation",
  year =         "2016",
  editor =       "Tobias Friedrich",
  pages =        "725--732",
  keywords =     "genetic algorithms, genetic programming",
  month =        "20-24 " # jul,
  organisation = "SIGEVO",
  address =      "Denver, USA",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  isbn13 =       "978-1-4503-4206-3",
  DOI =          "doi:10.1145/2908812.2908958",
  abstract =     "In this study we use Genetic Programming (GP) as an
                 offline hyper-heuristic to evolve a mutation operator
                 for Evolutionary Programming. This is done using the
                 Gaussian and uniform distributions as the terminal set,
                 and arithmetic operators as the function set. The
                 mutation operators are automatically designed for a
                 specific function class. The contribution of this paper
                 is to show that a GP can not only automatically design
                 a mutation operator for Evolutionary Programming (EP)
                 on functions generated from a specific function class,
                 but also can design more general mutation operators on
                 functions generated from groups of function classes. In
                 addition, the automatically designed mutation operators
                 also show good performance on new functions generated
                 from a specific function class or a group of function
                 classes.",
  notes =        "University of Nottingham

                 GECCO-2016 A Recombination of the 25th International
                 Conference on Genetic Algorithms (ICGA-2016) and the
                 21st Annual Genetic Programming Conference (GP-2016)",
}

Genetic Programming entries for Libin Hong

Citations