Guidelines for defining benchmark problems in Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "Miguel Nicolau and Alexandros Agapitos and 
                 Michael O'Neill and Anthony Brabazon",
  title =        "Guidelines for defining benchmark problems in Genetic
  booktitle =    "Proceedings of 2015 IEEE Congress on Evolutionary
                 Computation (CEC 2015)",
  editor =       "Yadahiko Murata",
  pages =        "1152--1159",
  year =         "2015",
  address =      "Sendai, Japan",
  month =        "25-28 " # may,
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/CEC.2015.7257019",
  abstract =     "The field of Genetic Programming has recently seen a
                 surge of attention to the fact that benchmarking and
                 comparison of approaches is often done in non-standard
                 ways, using poorly designed comparison problems. We
                 raise some issues concerning the design of benchmarks,
                 within the domain of symbolic regression, through
                 experimental evidence. A set of guidelines is provided,
                 aiming towards careful definition and use of artificial
                 functions as symbolic regression benchmarks.",
  notes =        "1145 hrs 15594 CEC2015",

Genetic Programming entries for Miguel Nicolau Alexandros Agapitos Michael O'Neill Anthony Brabazon