Structural Versus Evaluation Based Solutions Similarity in Genetic Programming Based System Identification

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

@InProceedings{DBLP:conf/nicso/Winkler10,
  author =       "Stephan M. Winkler",
  title =        "Structural Versus Evaluation Based Solutions
                 Similarity in Genetic Programming Based System
                 Identification",
  booktitle =    "Nature Inspired Cooperative Strategies for
                 Optimization, NICSO 2010",
  editor =       "Juan Ram{\'o}n Gonz{\'a}lez and David A. Pelta and 
                 Carlos Cruz and Germ{\'a}n Terrazas and 
                 Natalio Krasnogor",
  series =       "Studies in Computational Intelligence",
  volume =       "284",
  year =         "2010",
  pages =        "269--282",
  address =      "Granada, Spain",
  month =        may # " 12-14",
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-3-642-12537-9",
  DOI =          "doi:10.1007/978-3-642-12538-6_23",
  size =         "14 pages",
  bibsource =    "DBLP, http://dblp.uni-trier.de",
  abstract =     "Estimating the similarity of solution candidates
                 represented as structure trees is an important point in
                 the context of many genetic programming (GP)
                 applications. For example, when it comes to observing
                 population diversity dynamics, solutions have to be
                 compared to each other. In the context of GP based
                 system identification, i.e., when mathematical
                 expressions are evolved, solutions can be compared to
                 each other with respect to their structure as well as
                 to their evaluation. Obviously, structural similarity
                 estimation of formula trees is not equivalent to
                 evaluation based similarity estimation; we here want to
                 see whether there is a significant correlation between
                 the results calculated using these two approaches. In
                 order to get an overview regarding this issue, we have
                 analyzed a series of GP tests including both similarity
                 estimation strategies; in this paper we describe the
                 similarity estimation methods as well as the test data
                 sets used in these tests, and we document the results
                 of these tests. We see that in most cases there is a
                 significant positive linear correlation for the results
                 returned by the evaluation based and structural
                 methods. Especially in some cases showing very low
                 structural similarity there can be significantly
                 different results when using the evaluation based
                 similarity methods.",
  notes =        "NICSO",
}

Genetic Programming entries for Stephan M Winkler

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