Data Mining of Genetic Programming Run Logs

Created by W.Langdon from gp-bibliography.bib Revision:1.8129

@InProceedings{eurogp07:ciesielski,

• author = "Vic Ciesielski and Xiang Li",
• title = "Data Mining of Genetic Programming Run Logs",
• editor = "Marc Ebner and Michael O'Neill and Anik\'o Ek\'art and Leonardo Vanneschi and Anna Isabel Esparcia-Alc\'azar",
• booktitle = "Proceedings of the 10th European Conference on Genetic Programming",
• publisher = "Springer",
• series = "Lecture Notes in Computer Science",
• volume = "4445",
• year = "2007",
• address = "Valencia, Spain",
• month = "11-13 " # apr,
• pages = "281--290",
• keywords = "genetic algorithms, genetic programming",
• ISBN = "3-540-71602-5",
• isbn13 = "978-3-540-71602-0",
• DOI = "doi:10.1007/978-3-540-71605-1_26",
• abstract = "We have applied a range of data mining techniques to a data base of log file records created from genetic programming runs on twelve different problems. We have looked for unexpected patterns, or golden nuggets in the data. Six were found. The main discoveries were a surprising amount of evaluation of duplicate programs across the twelve problems and one case of pathological behaviour which suggested a review of the genetic programming configuration. For problems with expensive fitness evaluation, the results suggest that there would be considerable speedup by caching evolved programs and fitness values. A data mining analysis performed routinely in a GP application could identify problems early and lead to more effective genetic programming applications.",
• notes = "Part of \cite{ebner:2007:GP} EuroGP'2007 held in conjunction with EvoCOP2007, EvoBIO2007 and EvoWorkshops2007",

}

Genetic Programming entries for Victor Ciesielski Xiang Li

Citations