Solving the Unknown Complexity Formula Problem with Genetic Programming

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

@InProceedings{conf/iwann/BatistaSSLR13,
  author =       "Rayco Batista and Eduardo Segredo and 
                 Carlos Segura and Coromoto Leon and Casiano Rodriguez",
  title =        "Solving the Unknown Complexity Formula Problem with
                 Genetic Programming",
  bibdate =      "2013-06-25",
  bibsource =    "DBLP,
                 http://dblp.uni-trier.de/db/conf/iwann/iwann2013-1.html#BatistaSSLR13",
  booktitle =    "Advances in Computational Intelligence - 12th
                 International Work-Conference on Artificial Neural
                 Networks, {IWANN} 2013, Puerto de la Cruz, Tenerife,
                 Spain, June 12-14, 2013, Proceedings, Part {I}",
  publisher =    "Springer",
  year =         "2013",
  volume =       "7902",
  editor =       "Ignacio Rojas and Gonzalo Joya Caparr{\'o}s and 
                 Joan Cabestany",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-3-642-38678-7",
  pages =        "232--240",
  series =       "Lecture Notes in Computer Science",
  URL =          "http://dx.doi.org/10.1007/978-3-642-38679-4",
  DOI =          "doi:10.1007/978-3-642-38679-4_22",
  abstract =     "The Unknown Complexity Formula Problem (ucfp) is a
                 particular case of the symbolic regression problem in
                 which an analytical complexity formula that fits with
                 data obtained by multiple executions of certain
                 algorithm must be given. In this work, a set of
                 modifications has been added to the standard Genetic
                 Programming (GP) algorithm to deal with the ucfp. This
                 algorithm has been applied to a set of well-known
                 benchmark functions of the symbolic regression problem.
                 Moreover, a real case of the ucfp has been tackled.
                 Experimental evaluation has demonstrated the good
                 behaviour of the proposed approach in obtaining high
                 quality solutions, even for a real instance of the
                 ucfp. Finally, it is worth pointing out that the best
                 published results for the majority of benchmark
                 functions have been improved.",
}

Genetic Programming entries for Rayco Batista Eduardo Segredo Carlos Segura Coromoto Leon Casiano Rodriguez

Citations