A (mu + lambda) - GP Algorithm and its use for Regression Problems

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@InProceedings{Costa:2006:ICTAI,
  author =       "E. O. Costa and A. Pozo",
  title =        "A (mu + lambda) - GP Algorithm and its use for
                 Regression Problems",
  booktitle =    "8th IEEE International Conference on Tools with
                 Artificial Intelligence, ICTAI '06",
  year =         "2006",
  pages =        "10--17",
  address =      "Arlington, VA, USA",
  month =        nov,
  publisher =    "IEEE",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "0-7695-2728-0",
  DOI =          "doi:10.1109/ICTAI.2006.6",
  abstract =     "The genetic programming (GP) is a powerful technique
                 for symbolic regression. However, because it is a new
                 area, many improvements can be obtained changing the
                 basic behaviour of the method. In this way, this work
                 develop a different genetic programming algorithm doing
                 some modifications on the classical GP algorithm and
                 adding some concepts of evolution strategies. The new
                 approach was evaluated using two instances of symbolic
                 regression problem - the binomial-3 problem (a tunably
                 difficult problem), proposed in (J.M. Daida et al.,
                 2001) and the problem of modelling software reliability
                 growth (an application of symbolic regression). The
                 discovered results were compared with the classical GP
                 algorithm. The symbolic regression problems obtained
                 excellent results and an improvement was detected using
                 the proposed approach",
  notes =        "Dept. of Comput. Sci., Fed. Univ. of Parana,
                 Curitiba",
}

Genetic Programming entries for Eduardo Oliveira Costa Aurora Trinidad Ramirez Pozo

Citations