- 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, theory",
- 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 scales.",
-
notes = "Mathematica source code at
http://library.wolfram.com/infocenter/MathSource/5163
See also http://www.cs.ucl.ac.uk/staff/W.Langdon/gp2lattice/gp2lattice.html",
