Genetic Programming: Semantic point mutation operator based on the partial derivative error

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{Graff:2014:ROPEC,
  author =       "Mario Graff and Juan J. Flores and 
                 Jose {Ortiz Bejar}",
  booktitle =    "IEEE International Autumn Meeting on Power,
                 Electronics and Computing (ROPEC 2014)",
  title =        "Genetic Programming: Semantic point mutation operator
                 based on the partial derivative error",
  year =         "2014",
  month =        nov,
  abstract =     "There is a great interest in the Genetic Programming
                 (GP) community to develop semantic genetic operators.
                 Most recent approaches includes the genetic programming
                 framework for symbolic regression called Error Space
                 Alignment GP, the geometric semantic operators, and our
                 previous work the semantic crossover based on the
                 partial derivative error. To the best of our knowledge,
                 there has not been a semantic genetic operator similar
                 to the point mutation. In this contribution, we start
                 filling this gap by proposing a semantic point mutation
                 based on the derivative of the error. This novel
                 operator complements our previous semantic crossover
                 and, as the results show, there is an improvement in
                 performance when this novel operator is used, and,
                 furthermore, the best performance in our setting is the
                 system that uses the semantic crossover and the
                 semantic point mutation.",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/ROPEC.2014.7036344",
  notes =        "Also known as \cite{7036344}",
}

Genetic Programming entries for Mario Graff Guerrero Juan J Flores Jose Ortiz Bejar

Citations