Quantum-Inspired Multi-gene Linear Genetic Programming Model for Regression Problems

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

@InProceedings{Strachan:2014:BRACIS,
  author =       "Guilherme C. Strachan and Adriano S. Koshiyama and 
                 Douglas M. Dias and Marley M. B. R. Vellasco and 
                 Marco A. C. Pacheco",
  booktitle =    "Brazilian Conference on Intelligent Systems (BRACIS
                 2014)",
  title =        "Quantum-Inspired Multi-gene Linear Genetic Programming
                 Model for Regression Problems",
  year =         "2014",
  month =        oct,
  pages =        "152--157",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/BRACIS.2014.37",
  size =         "6 pages",
  abstract =     "We propose the Quantum-Inspired Multi-Gene Linear
                 Genetic Programming (QIMuLGP), which is a
                 generalisation of Quantum-Inspired Linear Genetic
                 Programming (QILGP) model for symbolic regression.
                 QIMuLGP allows us to explore a different genotypic
                 representation (i.e. linear), and to use more than one
                 genotype per individual, combining their outputs using
                 least squares method (multi-gene approach). We used 11
                 benchmark problems to experimentally compare QIMuLGP
                 with: canonical tree Genetic Programming, Multi-Gene
                 tree-based GP (MGGP), and QILGP. QIMuLGP obtained
                 better results than QILGP in almost all experiments
                 performed. When compared to MGGP, QIMuLGP achieved
                 equivalent errors for some experiments with its run
                 time always shorter (up to 20 times and 8 times on
                 average), which is an important advantage in high
                 dimensional-scalable problems.",
  notes =        "Also known as \cite{6984823}",
}

Genetic Programming entries for Guilherme Cesario Strachan Adriano Soares Koshiyama Douglas Mota Dias Marley Maria Bernardes Rebuzzi Vellasco Marco Aurelio Cavalcanti Pacheco

Citations