Genetic Programming that Ensures Programs are Original

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

@InProceedings{Yuen:2009:cec,
  author =       "Shiu Yin Yuen and Shing Wa Leung",
  title =        "Genetic Programming that Ensures Programs are
                 Original",
  booktitle =    "2009 IEEE Congress on Evolutionary Computation",
  year =         "2009",
  editor =       "Andy Tyrrell",
  pages =        "860--866",
  address =      "Trondheim, Norway",
  month =        "18-21 " # may,
  organization = "IEEE Computational Intelligence Society",
  publisher =    "IEEE Press",
  isbn13 =       "978-1-4244-2959-2",
  file =         "P246.pdf",
  DOI =          "doi:10.1109/CEC.2009.4983035",
  abstract =     "Conventional genetic programming (GP) does not
                 guarantee no revisits, i.e., a program may be generated
                 for fitness evaluations more than one time. This is
                 clearly wasteful in applications that involve expensive
                 and/or time consuming fitness evaluations. This paper
                 proposes a new GP - non-revisiting genetic programming
                 NrGP - that guarantees that all programs generated is
                 original. The basic idea is to use memory to store all
                 programs generated. To increase efficiency in indexing
                 and storage, the memory is organized as an S-expression
                 trie. Since the number of solutions generated is modest
                 for applications involving expensive and/or time
                 consuming fitness evaluations, the extra memory needed
                 is manageable. GP and NrGP are compared using two GP
                 bench mark problems, namely, the symbolic regression
                 and the even N-parity problem. It is found that NrGP
                 outperforms GP, significantly reducing the
                 computational effort (CE) required. This clearly shows
                 the power of the idea of ensuring no revisits. It is
                 anticipated that the same non-revisiting idea can be
                 applied to other types of GP to enhance their
                 efficiency. A new CE measurement is also reported that
                 removes some statistical biases associated with the
                 conventional CE.",
  keywords =     "genetic algorithms, genetic programming",
  notes =        "CEC 2009 - A joint meeting of the IEEE, the EPS and
                 the IET. IEEE Catalog Number: CFP09ICE-CDR",
}

Genetic Programming entries for Kelvin Shiu-yin Yuen Shing Wa Leung

Citations