Open issues in genetic programming

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

@Article{ONeill:2010:GPEM,
  author =       "Michael O'Neill and Leonardo Vanneschi and 
                 Steven Gustafson and Wolfgang Banzhaf",
  title =        "Open issues in genetic programming",
  journal =      "Genetic Programming and Evolvable Machines",
  year =         "2010",
  volume =       "11",
  number =       "3/4",
  pages =        "339--363",
  month =        sep,
  note =         "Tenth Anniversary Issue: Progress in Genetic
                 Programming and Evolvable Machines",
  keywords =     "genetic algorithms, genetic programming",
  ISSN =         "1389-2576",
  DOI =          "doi:10.1007/s10710-010-9113-2",
  size =         "25 pages",
  abstract =     "It is approximately 50 years since the first
                 computational experiments were conducted in what has
                 become known today as the field of Genetic Programming
                 (GP), twenty years since John Koza named and
                 popularised the method, and ten years since the first
                 issue appeared of the Genetic Programming & Evolvable
                 Machines journal. In particular, during the past two
                 decades there has been a significant range and volume
                 of development in the theory and application of GP, and
                 in recent years the field has become increasingly
                 applied. There remain a number of significant open
                 issues despite the successful application of GP to a
                 number of challenging real-world problem domains and
                 progress in the development of a theory explaining the
                 behavior and dynamics of GP. These issues must be
                 addressed for GP to realise its full potential and to
                 become a trusted mainstream member of the computational
                 problem solving toolkit. In this paper we outline some
                 of the challenges and open issues that face researchers
                 and practitioners of GP. We hope this overview will
                 stimulate debate, focus the direction of future
                 research to deepen our understanding of GP, and further
                 the development of more powerful problem solving
                 algorithms.",
}

Genetic Programming entries for Michael O'Neill Leonardo Vanneschi Steven M Gustafson Wolfgang Banzhaf

Citations