Created by W.Langdon from gp-bibliography.bib Revision:1.2031
@InProceedings{silva:2005:CEC,
author = "Sara Silva and Ernesto Costa",
title = "Comparing Tree Depth Limits and Resource-Limited
{GP}",
booktitle = "Proceedings of the 2005 IEEE Congress on Evolutionary
Computation",
year = "2005",
editor = "David Corne and Zbigniew Michalewicz and
Marco Dorigo and Gusz Eiben and David Fogel and Carlos Fonseca and
Garrison Greenwood and Tan Kay Chen and
Guenther Raidl and Ali Zalzala and Simon Lucas and Ben Paechter and
Jennifier Willies and Juan J. Merelo Guervos and
Eugene Eberbach and Bob McKay and Alastair Channon and
Ashutosh Tiwari and L. Gwenn Volkert and
Dan Ashlock and Marc Schoenauer",
volume = "1",
pages = "920--927",
address = "Edinburgh, UK",
publisher_address = "445 Hoes Lane, P.O. Box 1331, Piscataway, NJ
08855-1331, USA",
month = "2-5 " # sep,
organisation = "IEEE Computational Intelligence Society, Institution
of Electrical Engineers (IEE), Evolutionary Programming
Society (EPS)",
publisher = "IEEE Press",
keywords = "genetic algorithms, genetic programming",
ISBN = "0-7803-9363-5",
abstract = "we compare two different approaches for controlling
bloat in Genetic Programming, tree depth limits and
resource-limited GP. Tree depth limits operate at the
individual level, avoiding excessive code growth by
imposing a maximum depth to each individual.
Resource-limited GP is a new technique that operates at
the population level, limiting the total amount of
resources the entire population can use. We compare
their dynamics and performance on three problems:
Symbolic Regression, Even Parity, and Artificial Ant.
The results suggest that resource-limited GP is
superior to tree depth limits, but we question this
superiority and discuss possible ways of combining the
strengths of both approaches, to further improve the
results.",
notes = "CEC2005 - A joint meeting of the IEEE, the IEE, and
the EPS.",
}
Genetic Programming entries for Sara Silva Ernesto Costa