Improving the Tartarus Problem as a Benchmark in Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4216

  author =       "Thomas D. Griffiths and Aniko Ekart",
  title =        "Improving the Tartarus Problem as a Benchmark in
                 Genetic Programming",
  booktitle =    "EuroGP 2017: Proceedings of the 20th European
                 Conference on Genetic Programming",
  year =         "2017",
  month =        "19-21 " # apr,
  editor =       "Mauro Castelli and James McDermott and 
                 Lukas Sekanina",
  series =       "LNCS",
  volume =       "10196",
  publisher =    "Springer Verlag",
  address =      "Amsterdam",
  pages =        "278--293",
  organisation = "species",
  keywords =     "genetic algorithms, genetic programming: Poster",
  DOI =          "doi:10.1007/978-3-319-55696-3_18",
  abstract =     "For empirical research on computer algorithms, it is
                 essential to have a set of benchmark problems on which
                 the relative performance of different methods and their
                 applicability can be assessed. In the majority of
                 computational research fields there are established
                 sets of benchmark problems; however, the field of
                 genetic programming lacks a similarly rigorously
                 defined set of benchmarks. There is a strong interest
                 within the genetic programming community to develop a
                 suite of benchmarks. Following recent surveys, the
                 desirable characteristics of a benchmark problem are
                 now better defined. In this paper the Tartarus problem
                 is proposed as a tunably difficult benchmark problem
                 for use in Genetic Programming. The justification for
                 this proposal is presented, together with guidance on
                 its usage as a benchmark.",
  notes =        "Part of \cite{Castelli:2017:GP} EuroGP'2017 held
                 inconjunction with EvoCOP2017, EvoMusArt2017 and

Genetic Programming entries for Thomas D Griffiths Aniko Ekart