Created by W.Langdon from gp-bibliography.bib Revision:1.2031
@InProceedings{murphy_etal:cec2010,
author = "Eoin Murphy and Michael O'Neill and
Edgar Galvan-Lopez and Anthony Brabazon",
title = "Tree-Adjunct Grammatical Evolution",
booktitle = "2010 IEEE World Congress on Computational
Intelligence",
pages = "4449--4456",
year = "2010",
address = "Barcelona, Spain",
month = "18-23 " # jul,
organization = "IEEE Computational Intelligence Society",
publisher = "IEEE Press",
keywords = "genetic algorithms, genetic programming, grammatical
evolution, TAG",
isbn13 = "978-1-4244-6910-9",
doi = "
doi:10.1109/CEC.2010.5586497",
size = "8 pages",
abstract = "In this paper we investigate the application of
tree-adjunct grammars to grammatical evolution. The
standard type of grammar used by grammatical evolution,
context-free grammars, produce a subset of the
languages that tree-adjunct grammars can produce,
making tree-adjunct grammars, expressively, more
powerful. In this study we shed some light on the
effects of tree-adjunct grammars on grammatical
evolution, or tree-adjunct grammatical evolution. We
perform an analytic comparison of the performance of
both setups, i.e., grammatical evolution and
tree-adjunct grammatical evolution, across a number of
classic genetic programming benchmarking problems. The
results firmly indicate that tree-adjunct grammatical
evolution has a better overall performance (measured in
terms of finding the global optima).",
notes = "adjunction is the only composition operator, TAG3P
alpha trees. Auxiliary trees= beta trees. Elementary
trees. TAGE (fixed chromosome length). GEVA v1.1.
Even-5-parity, Santa Fe Ant, symbolic regression,
6-Mux, Max problem \cite{Gathercole:1996:aicrtd}
\cite{langdon:1997:MAX}. WCCI 2010. Also known as
\cite{5586497}",
}
Genetic Programming entries for Eoin Murphy Michael O'Neill Edgar Galvan Lopez Anthony Brabazon