Memetic Genetic Programming based on orthogonal projections in the phenotype space

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

@InProceedings{Graff:2015:ROPEC,
  author =       "Mario Graff and Eric S. Tellez and 
                 Hugo Jair Escalante and Jose Ortiz-Bejar",
  booktitle =    "2015 IEEE International Autumn Meeting on Power,
                 Electronics and Computing (ROPEC)",
  title =        "Memetic Genetic Programming based on orthogonal
                 projections in the phenotype space",
  year =         "2015",
  abstract =     "Genetic Programming (GP) is an evolutionary algorithm
                 that has received a lot of attention lately due to its
                 success in solving hard real-world problems. Lately,
                 there has been a great interest in GP's community to
                 develop semantic genetic operators, i.e., operators
                 that work on the phenotype. In this contribution, we
                 improve the performance of GP by making orthogonal
                 projections in the phenotype space using the behaviour
                 of the parents and the target, i.e., the problem at
                 hand. The technique proposed can be easily applied to
                 any tree based GP, and, as the result show this
                 technique statistically improves the performance of GP.
                 Furthermore, we experimentally show how a traditional
                 GP system enhanced with our technique can outperform
                 the state of the art geometric semantic GP systems.",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/ROPEC.2015.7395160",
  month =        nov,
  notes =        "Also known as \cite{7395160}",
}

Genetic Programming entries for Mario Graff Guerrero Eric Sadit Tellez Hugo Jair Escalante Jose Ortiz Bejar

Citations