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

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@Article{Castelli:2013:ieeeCybernetics,
  author =       "Mauro Castelli and Leonardo Vanneschi and Sara Silva",
  journal =      "IEEE Transactions on Cybernetics",
  title =        "Semantic Search-Based Genetic Programming and the
                 Effect of Intron Deletion",
  year =         "2014",
  volume =       "44",
  number =       "1",
  pages =        "103--113",
  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.",
  keywords =     "genetic algorithms, genetic programming,
                 Generalisation, genetic programming (GP), introns,
                 semantics",
  DOI =          "doi:10.1109/TSMCC.2013.2247754",
  ISSN =         "2168-2267",
  notes =        "Also known as \cite{6476653}",
}

Genetic Programming entries for Mauro Castelli Leonardo Vanneschi Sara Silva

Citations