Visualizing Tree Structures in Genetic Programming

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  author =       "Jason M. Daida and Adam M. Hilss and David J. Ward and 
                 Stephen L. Long",
  title =        "Visualizing Tree Structures in Genetic Programming",
  journal =      "Genetic Programming and Evolvable Machines",
  year =         "2005",
  volume =       "6",
  number =       "1",
  pages =        "79--110",
  month =        mar,
  keywords =     "genetic algorithms, genetic programming",
  ISSN =         "1389-2576",
  doi =          "doi:10.1007/s10710-005-7621-2",
  size =         "32 pages",
  abstract =     "This paper presents methods to visualise the structure
                 of trees that occur in genetic programming. These
                 methods allow for the inspection of structure of entire
                 trees even though several thousands of nodes may be
                 involved. The methods also scale to allow for the
                 inspection of structure for entire populations and for
                 complete trials even though millions of nodes may be
                 involved. Examples are given that demonstrate how this
                 new way of seeing can afford a potentially rich way of
                 understanding dynamics that underpin genetic
                 programming. The examples indicate further studies that
                 might be enabled by visualising structure at these
  notes =        "Mathematica source code at

                 See also

Genetic Programming entries for Jason M Daida Adam M Hilss David J Ward Stephen L Long

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