The effects of size and depth limits on tree based
genetic programming
E. Crane, and N. McPhee. Genetic Programming Theory and Practice III, volume 9 of Genetic Programming, chapter 15, Springer, Ann Arbor, (12-14 May 2005)
Abstract
Bloat is a common and well studied problem in genetic
programming. Size and depth limits are often used to
combat bloat, but to date there has been little
detailed exploration of the effects and biases of such
limits. In this paper we present empirical analysis of
the effects of size and depth limits on binary tree
genetic programs. We find that size limits control
population average size in much the same way as depth
limits do. Our data suggests, however that size limits
provide finer and more reliable control than depth
limits, which has less of an impact upon tree shapes.
%0 Book Section
%1 crane:2005:GPTP
%A Crane, Ellery Fussell
%A McPhee, Nicholas Freitag
%B Genetic Programming Theory and Practice III
%C Ann Arbor
%D 2005
%E Yu, Tina
%E Riolo, Rick L.
%E Worzel, Bill
%I Springer
%K Depth Population Shape, Size Tree algorithms, bloat distributions, genetic limits, programming,
%P 223--240
%T The effects of size and depth limits on tree based
genetic programming
%V 9
%X Bloat is a common and well studied problem in genetic
programming. Size and depth limits are often used to
combat bloat, but to date there has been little
detailed exploration of the effects and biases of such
limits. In this paper we present empirical analysis of
the effects of size and depth limits on binary tree
genetic programs. We find that size limits control
population average size in much the same way as depth
limits do. Our data suggests, however that size limits
provide finer and more reliable control than depth
limits, which has less of an impact upon tree shapes.
%& 15
%@ 0-387-28110-X
@incollection{crane:2005:GPTP,
abstract = {Bloat is a common and well studied problem in genetic
programming. Size and depth limits are often used to
combat bloat, but to date there has been little
detailed exploration of the effects and biases of such
limits. In this paper we present empirical analysis of
the effects of size and depth limits on binary tree
genetic programs. We find that size limits control
population average size in much the same way as depth
limits do. Our data suggests, however that size limits
provide finer and more reliable control than depth
limits, which has less of an impact upon tree shapes.},
added-at = {2008-06-19T17:35:00.000+0200},
address = {Ann Arbor},
author = {Crane, Ellery Fussell and McPhee, Nicholas Freitag},
biburl = {https://www.bibsonomy.org/bibtex/26cb86941c18b04877ae431bc859f4d74/brazovayeye},
booktitle = {Genetic Programming Theory and Practice {III}},
chapter = 15,
editor = {Yu, Tina and Riolo, Rick L. and Worzel, Bill},
interhash = {9eadc7447986ed3646061bf025438fff},
intrahash = {6cb86941c18b04877ae431bc859f4d74},
isbn = {0-387-28110-X},
keywords = {Depth Population Shape, Size Tree algorithms, bloat distributions, genetic limits, programming,},
month = {12-14 May},
notes = {part of \cite{yu:2005:GPTP} Published Jan 2006 after
the workshop},
pages = {223--240},
publisher = {Springer},
series = {Genetic Programming},
size = {18 pages},
timestamp = {2008-06-19T17:38:12.000+0200},
title = {The effects of size and depth limits on tree based
genetic programming},
volume = 9,
year = 2005
}