Adjudicated GP: A Behavioural Approach to Selective Breeding

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{Fitzgerald:2015:FSOWrevised,
  author =       "Jeannie M. Fitzgerald and Conor Ryan",
  title =        "Adjudicated GP: A Behavioural Approach to Selective
                 Breeding",
  booktitle =    "The 7th International Joint Conference on
                 Computational Intelligence (IJCCI 2015)",
  year =         "2015",
  editor =       "Juan Julian Merelo and Agostinho Rosa and 
                 Jose M. Cadenas and Antonio Dourado Correia and 
                 Kurosh Madani and Antonio Ruano and Joaquim Filipe",
  volume =       "669",
  series =       "Studies in Computational Intelligence",
  pages =        "135--154",
  address =      "Lisbon, Portugal",
  month =        nov # " 12-14",
  organisation = "INSTICC",
  publisher =    "Springer",
  note =         "Revised Selected Papers",
  keywords =     "genetic algorithms, genetic programming, Program
                 semantics, Selective breeding",
  isbn13 =       "978-3-319-48506-5",
  DOI =          "doi:10.1007/978-3-319-48506-5_8",
  abstract =     "For some time, there has been a realisation among
                 Genetic Programming researchers that relying on a
                 single scalar fitness value to drive evolutionary
                 search is no longer a satisfactory approach. Instead,
                 efforts are being made to gain richer insights into the
                 complexity of program behaviour. To this end,
                 particular attention has been focused on the notion of
                 semantic space. In this paper we propose and unified
                 hierarchical approach which decomposes program
                 behaviour into semantic, result and adjudicated spaces,
                 where adjudicated space sits at the top of the
                 behavioural hierarchy and represents an abstraction of
                 program behaviour that focuses on the success or
                 failure of candidate solutions in solving problem
                 sub-components. We show that better, smaller solutions
                 are discovered when crossover is directed in
                 adjudicated space. We investigate the effectiveness of
                 several possible adjudicated strategies on a variety of
                 classification and symbolic regression problems, and
                 show that both of our novel pillage and barter tactics
                 significantly outperform both a standard genetic
                 programming and an enhanced genetic programming
                 configuration on the fourteen problems studied. The
                 proposed method is extremely effective when
                 incorporated into a standard Genetic Programming
                 structure but should also complement several other
                 semantic approaches proposed in the literature.",
  notes =        "Published by Springer 2017. See
                 \cite{Fitzgerald:2015:FSOW}

                 Biocomputing and Developmental Systems Group,
                 University of Limerick, Limerick, Ireland",
}

Genetic Programming entries for Jeannie Fitzgerald Conor Ryan

Citations