A Data Structure for Improved GP Analysis via Efficient Computation and Visualisation of Population Measures

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{ekart:2004:eurogp,

• author = "Aniko Ekart and Steven Gustafson",
• title = "A Data Structure for Improved GP Analysis via Efficient Computation and Visualisation of Population Measures",
• booktitle = "Genetic Programming 7th European Conference, EuroGP 2004, Proceedings",
• year = "2004",
• editor = "Maarten Keijzer and Una-May O'Reilly and Simon M. Lucas and Ernesto Costa and Terence Soule",
• volume = "3003",
• series = "LNCS",
• pages = "35--46",
• address = "Coimbra, Portugal",
• publisher_address = "Berlin",
• month = "5-7 " # apr,
• organisation = "EvoNet",
• publisher = "Springer-Verlag",
• keywords = "genetic algorithms, genetic programming",
• ISBN = "3-540-21346-5",
• URL = "http://www.sztaki.hu/~ekart/eurgp4.ps",
• URL = "http://www.cs.nott.ac.uk/~smg/research/publications/eurogp-itree-2004.pdf",
• DOI = "doi:10.1007/978-3-540-24650-3_4",
• abstract = "Population measures for genetic programs are defined and analysed in an attempt to better understand the behaviour of genetic programming. Some measures are simple, but do not provide sufficient insight. The more meaningful ones are complex and take extra computation time. Here we present a unified view on the computation of population measures through an information hyper-tree (iTree). The iTree allows for a unified and efficient calculation of population measures via a basic tree traversal.",
• notes = "Part of \cite{keijzer:2004:GP} EuroGP'2004 held in conjunction with EvoCOP2004 and EvoWorkshops2004",

}

Genetic Programming entries for Aniko Ekart Steven M Gustafson

Citations