A Relaxed Approach to Simplification in Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{Johnston:2010:EuroGP,
-
author = "Mark Johnston and Thomas Liddle and Mengjie Zhang",
-
title = "A Relaxed Approach to Simplification in Genetic
Programming",
-
booktitle = "Proceedings of the 13th European Conference on Genetic
Programming, EuroGP 2010",
-
year = "2010",
-
editor = "Anna Isabel Esparcia-Alcazar and Aniko Ekart and
Sara Silva and Stephen Dignum and A. Sima Uyar",
-
volume = "6021",
-
series = "LNCS",
-
pages = "110--121",
-
address = "Istanbul",
-
month = "7-9 " # apr,
-
organisation = "EvoStar",
-
publisher = "Springer",
-
keywords = "genetic algorithms, genetic programming",
-
isbn13 = "978-3-642-12147-0",
-
DOI = "doi:10.1007/978-3-642-12148-7_10",
-
abstract = "We propose a novel approach to program simplification
in tree-based Genetic Programming, based upon numerical
relaxations of algebraic rules. We also separate
proposal of simplifications from an acceptance
criterion that checks the effect of proposed
simplifications on the evaluation of training examples,
looking several levels up the tree. We test our
simplification method on three classification datasets
and conclude that the success of linear regression is
dataset dependent, that looking further up the tree can
catch ineffective simplifications, and that CPU time
can be significantly reduced while maintaining
classification accuracy on unseen examples.",
-
notes = "Part of \cite{Esparcia-Alcazar:2010:GP} EuroGP'2010
held in conjunction with EvoCOP2010 EvoBIO2010 and
EvoApplications2010",
- }
Genetic Programming entries for
Mark Johnston
Thomas Liddle
Mengjie Zhang
Citations