How Far Is It From Here to There? A Distance that is Coherent with GP Operators

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

@InProceedings{mcdermott:2011:EuroGP,
  author =       "James McDermott and Una-May O'Reilly and 
                 Leonardo Vanneschi and Kalyan Veeramachaneni",
  title =        "How Far Is It From Here to There? A Distance that is
                 Coherent with GP Operators",
  booktitle =    "Proceedings of the 14th European Conference on Genetic
                 Programming, EuroGP 2011",
  year =         "2011",
  month =        "27-29 " # apr,
  editor =       "Sara Silva and James A. Foster and Miguel Nicolau and 
                 Mario Giacobini and Penousal Machado",
  series =       "LNCS",
  volume =       "6621",
  publisher =    "Springer Verlag",
  address =      "Turin, Italy",
  pages =        "190--202",
  organisation = "EvoStar",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-3-642-20406-7",
  DOI =          "doi:10.1007/978-3-642-20407-4_17",
  abstract =     "The distance between pairs of individuals is a useful
                 concept in the study of evolutionary algorithms. It is
                 particularly useful to define a distance which is
                 coherent with, i.e. related to, the action of a
                 particular operator. We present the first formal,
                 general definition of this operator-distance coherence.
                 We also propose a new distance function, based on the
                 multi-step transition probability (MSTP), that is
                 coherent with any GP operator for which the one-step
                 transition probability (1STP) between individuals can
                 be defined. We give an algorithm for 1STP in the case
                 of subtree mutation. Because MSTP is useful in GP
                 investigations, but impractical to compute, we evaluate
                 a variety of means to approximate it. We show that some
                 syntactic distance measures give good approximations,
                 and attempt to combine them to improve the
                 approximation using a GP symbolic regression method. We
                 conclude that 1STP itself is a sufficient indicator of
                 MSTP for subtree mutation.",
  notes =        "

                 Hill climber. x*x+x*y on unit square. 15 syntactic
                 distances. Cf \cite{blickle:thesis}.

                 Part of \cite{Silva:2011:GP} EuroGP'2011 held in
                 conjunction with EvoCOP2011 EvoBIO2011 and
                 EvoApplications2011",
}

Genetic Programming entries for James McDermott Una-May O'Reilly Leonardo Vanneschi Kalyan Veeramachaneni

Citations