Semantic Search-Based Genetic Programming and the Effect of Intron Deletion

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

@Article{Castelli:2014:ieeeCybernetics,
  author =       "Mauro Castelli and Leonardo Vanneschi and Sara Silva",
  title =        "Semantic Search-Based Genetic Programming and the
                 Effect of Intron Deletion",
  journal =      "IEEE Transactions on Cybernetics",
  year =         "2014",
  volume =       "44",
  number =       "1",
  pages =        "103--113",
  month =        jan,
  keywords =     "genetic algorithms, genetic programming,
                 Generalisation, introns, semantics",
  ISSN =         "2168-2267",
  DOI =          "doi:10.1109/TSMCC.2013.2247754",
  size =         "11 pages",
  abstract =     "The concept of semantics (in the sense of input-output
                 behaviour of solutions on training data) has been the
                 subject of a noteworthy interest in the genetic
                 programming (GP) research community over the past few
                 years. In this paper, we present a new GP system that
                 uses the concept of semantics to improve search
                 effectiveness. It maintains a distribution of different
                 semantic behaviours and biases the search toward
                 solutions that have similar semantics to the best
                 solutions that have been found so far. We present
                 experimental evidence of the fact that the new
                 semantics-based GP system outperforms the standard GP
                 and the well-known bacterial GP on a set of test
                 functions, showing particularly interesting results for
                 noncontinuous (i.e., generally harder to optimise) test
                 functions. We also observe that the solutions generated
                 by the proposed GP system often have a larger size than
                 the ones returned by standard GP and bacterial GP and
                 contain an elevated number of introns, i.e., parts of
                 code that do not have any effect on the semantics.
                 Nevertheless, we show that the deletion of introns
                 during the evolution does not affect the performance of
                 the proposed method.",
  notes =        "Author list corrected as:
                 doi:10.1109/TCYB.2014.2303551 Also known as
                 \cite{6476653}",
}

Genetic Programming entries for Mauro Castelli Leonardo Vanneschi Sara Silva

Citations