- author = "Jens Niehaus and Wolfgang Banzhaf",
- title = "Adaption of Operator Probabilities in Genetic Programming",
- booktitle = "Genetic Programming, Proceedings of EuroGP'2001",
- year = "2001",
- editor = "Julian F. Miller and Marco Tomassini and Pier Luca Lanzi and Conor Ryan and Andrea G. B. Tettamanzi and William B. Langdon",
- volume = "2038",
- series = "LNCS",
- pages = "325--336",
- address = "Lake Como, Italy",
- publisher_address = "Berlin",
- month = "18-20 " # apr,
- organisation = "EvoNET",
- publisher = "Springer-Verlag",
- keywords = "genetic algorithms, genetic programming, Adaptation, Adaption, Structure Optimisation: Poster",
- ISBN = "3-540-41899-7",
-
URL = "
http://neo.lcc.uma.es/EAWebSite/SKELETON/GPROG/eurogp01-2.ps.gz",
-
URL = "
http://www.springerlink.com/openurl.asp?genre=article&issn=0302-9743&volume=2038&spage=325",
-
DOI = "
doi:10.1007/3-540-45355-5_26",
- size = "12 pages",
-
abstract = "In this work we tried to reduce the number of free
parameters within Genetic Programming without reducing
the quality of the results. We developed three new
methods to adapt the probabilities, different genetic
operators are applied with. Using two problems from the
areas of symbolic regression and classification we
showed that the results in these cases were better than
randomly chosen parameter sets and could compete with
parameter sets chosen with empirical knowledge.
",
- notes = "EuroGP'2001, part of \cite{miller:2001:gp}",
