GP vs GI: if you can't beat them, join them

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "John Woodward and Colin Johnson and 
                 Alexander Brownlee",
  title =        "GP vs GI: if you can't beat them, join them",
  booktitle =    "Genetic Improvement 2016 Workshop",
  year =         "2016",
  editor =       "Justyna Petke and David R. White and Westley Weimer",
  pages =        "1155--1156",
  address =      "Denver",
  publisher_address = "New York, NY, USA",
  month =        jul # " 20-24",
  organisation = "SIGEvo",
  publisher =    "ACM",
  keywords =     "genetic algorithms, genetic programming, Genetic
                 Improvement, SBSE",
  URL =          "",
  DOI =          "doi:10.1145/2908961.2931694",
  size =         "2 pages",
  abstract =     "Genetic Programming (GP) has been criticized for
                 targeting irrelevant problems [12], and is also true of
                 the wider machine learning community [11]. which has
                 become detached from the source of the data it is using
                 to drive the field forward. However, recently GI
                 provides a fresh perspective on automated programming.
                 In contrast to GP, GI begins with existing software,
                 and therefore immediately has the aim of tackling real
                 software. As evolution is the main approach to GI to
                 manipulating programs, this connection with real
                 software should persuade the GP community to confront
                 the issues around what it originally set out to tackle
                 i.e. evolving real software.",
  notes =        "GECCO 2016 Workshop

Genetic Programming entries for John R Woodward Colin G Johnson Alexander E I Brownlee