Two Fast Tree-Creation Algorithms for Genetic
Programming
S. Luke. IEEE Transactions on Evolutionary Computation, 4 (3):
274--283(September 2000)
Abstract
Genetic programming is an evolutionary optimization
method that produces functional programs to solve a
given task. These programs commonly take the form of
trees representing LISP s-expressions, and a typical
evolutionary run produces a great many of these trees.
For this reason, a good tree generation algorithm is
very important to genetic programming. This paper
presents two new tree-generation algorithms for genetic
programming and for strongly-typed genetic programming,
a common variant. These algorithms are fast, allow the
user to request specific tree sizes, and guarantee
probabilities of certain nodes appearing in trees. The
paper analyzes these two algorithms and compares them
with traditional and recently proposed approaches.
%0 Journal Article
%1 luke:2000:2ftcaGP
%A Luke, Sean
%D 2000
%J IEEE Transactions on Evolutionary Computation
%K Bloat Creation, Growth, Initialization, Introns, Mutation, Population Subtree Tree algorithms, genetic programming,
%N 3
%P 274--283
%T Two Fast Tree-Creation Algorithms for Genetic
Programming
%U http://citeseer.ist.psu.edu/409667.html
%V 4
%X Genetic programming is an evolutionary optimization
method that produces functional programs to solve a
given task. These programs commonly take the form of
trees representing LISP s-expressions, and a typical
evolutionary run produces a great many of these trees.
For this reason, a good tree generation algorithm is
very important to genetic programming. This paper
presents two new tree-generation algorithms for genetic
programming and for strongly-typed genetic programming,
a common variant. These algorithms are fast, allow the
user to request specific tree sizes, and guarantee
probabilities of certain nodes appearing in trees. The
paper analyzes these two algorithms and compares them
with traditional and recently proposed approaches.
@article{luke:2000:2ftcaGP,
abstract = {Genetic programming is an evolutionary optimization
method that produces functional programs to solve a
given task. These programs commonly take the form of
trees representing LISP s-expressions, and a typical
evolutionary run produces a great many of these trees.
For this reason, a good tree generation algorithm is
very important to genetic programming. This paper
presents two new tree-generation algorithms for genetic
programming and for strongly-typed genetic programming,
a common variant. These algorithms are fast, allow the
user to request specific tree sizes, and guarantee
probabilities of certain nodes appearing in trees. The
paper analyzes these two algorithms and compares them
with traditional and recently proposed approaches.},
added-at = {2008-06-19T17:35:00.000+0200},
author = {Luke, Sean},
biburl = {https://www.bibsonomy.org/bibtex/2788f8ce76795eab433443e38bb61b417/brazovayeye},
interhash = {ae9f9a3a7c853e3db8ef4b656cd2713f},
intrahash = {788f8ce76795eab433443e38bb61b417},
journal = {IEEE Transactions on Evolutionary Computation},
keywords = {Bloat Creation, Growth, Initialization, Introns, Mutation, Population Subtree Tree algorithms, genetic programming,},
month = {September},
number = 3,
pages = {274--283},
size = {9 pages},
timestamp = {2008-06-19T17:45:57.000+0200},
title = {Two Fast Tree-Creation Algorithms for Genetic
Programming},
url = {http://citeseer.ist.psu.edu/409667.html},
volume = 4,
year = 2000
}