Genetic Programming with Guaranteed Quality

author = "Stefan Droste",

title = "Genetic Programming with Guaranteed Quality",

booktitle = "Genetic Programming 1998: Proceedings of the Third Annual Conference",

year = "1998",

editor = "John R. Koza and Wolfgang Banzhaf and Kumar Chellapilla and Kalyanmoy Deb and Marco Dorigo and David B. Fogel and Max H. Garzon and David E. Goldberg and Hitoshi Iba and Rick Riolo",

pages = "54--59",

address = "University of Wisconsin, Madison, Wisconsin, USA",

publisher_address = "San Francisco, CA, USA",

month = "22-25 " # jul,

publisher = "Morgan Kaufmann",

keywords = "genetic algorithms, genetic programming",

ISBN = "1-55860-548-7",

URL = "

https://eldorado.uni-dortmund.de/dspace/bitstream/2003/5321/2/ci1597_doc.pdf",

URL = "

http://citeseer.ist.psu.edu/324287.html",

abstract = "When using genetic programming (GP) or other techniques that try to approximate unknown functions, the principle of Occam's razor is often applied: find the simplest function that explains the given data, as it is assumed to be the best approximation for the unknown function. Using a well-known result from learning theory, it is shown in this paper, how Occam's razor can help GP in finding functions, so that the number of functions that differ from the unknown function by more than a certain degree can be bounded theoretically. Experiments show how these bounds can be used to get guaranteed quality assurances for practical applications, even though they are much too conservative.",

notes = "GP-98",