A Framework for the Empirical Analysis of Genetic Programming System Performance

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

  author =       "Oliver Flasch and Thomas Bartz-Beielstein",
  title =        "A Framework for the Empirical Analysis of Genetic
                 Programming System Performance",
  booktitle =    "Genetic Programming Theory and Practice X",
  year =         "2012",
  series =       "Genetic and Evolutionary Computation",
  editor =       "Rick Riolo and Ekaterina Vladislavleva and 
                 Marylyn D. Ritchie and Jason H. Moore",
  publisher =    "Springer",
  chapter =      "11",
  pages =        "155--169",
  address =      "Ann Arbor, USA",
  month =        "12-14 " # may,
  keywords =     "genetic algorithms, genetic programming, Symbolic
                 regression, Design of experiments, Sequential parameter
                 optimisation, Reproducible research, Multi-objective
  isbn13 =       "978-1-4614-6845-5",
  URL =          "http://dx.doi.org/10.1007/978-1-4614-6846-2_11",
  DOI =          "doi:10.1007/978-1-4614-6846-2_11",
  abstract =     "This chapter introduces a framework for statistically
                 sound, reproducible empirical research in Genetic
                 Programming (GP). It provides tools to understand GP
                 algorithms and heuristics and their interaction with
                 problems of varying difficulty. Following an approach
                 where scientific claims are broken down to testable
                 statistical hypotheses and GP runs are treated as
                 experiments, the framework helps to achieve
                 statistically verified results of high
  notes =        "part of \cite{Riolo:2012:GPTP} published after the
                 workshop in 2013",

Genetic Programming entries for Oliver Flasch Thomas Bartz-Beielstein