Experiments with Explicit For-loops in Genetic
Programming
V. Ciesielski, and X. Li. Proceedings of the 2004 IEEE Congress on Evolutionary
Computation, page 494--501. Portland, Oregon, IEEE Press, (20-23 June 2004)
Abstract
Evolving programs with explicit loops presents major
difficulties, primarily due to the massive increase in
the size of the search space. Fitness evaluation
becomes computationally expensive. We have investigated
ways of dealing with these poblems by the evolution of
for-loops of increasing semantic complexity. We have
chosen two problems -- a modified Santa Fe ant problem
and a sorting problem -- which have natural looping
constructs in their solution and a solution without
loops is not possible unless the tree depth is very
large. We have shown that by conrolling the complexity
of the loop structures it is possible to evolve smaller
and more understandable programs for these problems.
%0 Conference Paper
%1 ciesielski:2004:ewefigp
%A Ciesielski, Vic
%A Li, Xiang
%B Proceedings of the 2004 IEEE Congress on Evolutionary
Computation
%C Portland, Oregon
%D 2004
%I IEEE Press
%K Theory algorithms algorithms, evolutionary genetic of programming,
%P 494--501
%T Experiments with Explicit For-loops in Genetic
Programming
%X Evolving programs with explicit loops presents major
difficulties, primarily due to the massive increase in
the size of the search space. Fitness evaluation
becomes computationally expensive. We have investigated
ways of dealing with these poblems by the evolution of
for-loops of increasing semantic complexity. We have
chosen two problems -- a modified Santa Fe ant problem
and a sorting problem -- which have natural looping
constructs in their solution and a solution without
loops is not possible unless the tree depth is very
large. We have shown that by conrolling the complexity
of the loop structures it is possible to evolve smaller
and more understandable programs for these problems.
%@ 0-7803-8515-2
@inproceedings{ciesielski:2004:ewefigp,
abstract = {Evolving programs with explicit loops presents major
difficulties, primarily due to the massive increase in
the size of the search space. Fitness evaluation
becomes computationally expensive. We have investigated
ways of dealing with these poblems by the evolution of
for-loops of increasing semantic complexity. We have
chosen two problems -- a modified Santa Fe ant problem
and a sorting problem -- which have natural looping
constructs in their solution and a solution without
loops is not possible unless the tree depth is very
large. We have shown that by conrolling the complexity
of the loop structures it is possible to evolve smaller
and more understandable programs for these problems.},
added-at = {2008-06-19T17:35:00.000+0200},
address = {Portland, Oregon},
author = {Ciesielski, Vic and Li, Xiang},
biburl = {https://www.bibsonomy.org/bibtex/245202bc8651e7d0aa782816efcfa1bd9/brazovayeye},
booktitle = {Proceedings of the 2004 IEEE Congress on Evolutionary
Computation},
interhash = {910be17510e3700a878509b9609789ac},
intrahash = {45202bc8651e7d0aa782816efcfa1bd9},
isbn = {0-7803-8515-2},
keywords = {Theory algorithms algorithms, evolutionary genetic of programming,},
month = {20-23 June},
notes = {CEC 2004 - A joint meeting of the IEEE, the EPS, and
the IEE.},
pages = {494--501},
publisher = {IEEE Press},
timestamp = {2008-06-19T17:37:56.000+0200},
title = {Experiments with Explicit For-loops in Genetic
Programming},
year = 2004
}