M. Keijzer, C. Ryan, M. O'Neill, M. Cattolico, and V. Babovic. Genetic Programming, Proceedings of EuroGP'2001, volume 2038 of LNCS, page 74--86. Lake Como, Italy, Springer-Verlag, (18-20 April 2001)
Abstract
This paper isolates and identifies the effects of the
crossover operator used in Grammatical Evolution. This
crossover operator has already been shown to be adept
at combining useful building blocks and to outperform
engineered crossover operators such as Homologous
Crossover. This crossover operator, Ripple Crossover is
described in terms of Genetic Programming and applied
to two benchmark problems.
Its performance is compared with that of traditional
sub-tree crossover on populations employing the
standard functions and terminal set, but also against
populations of individuals that encode Context Free
Grammars. Ripple crossover is more effective in
exploring the search space of possible programs than
sub-tree crossover. This is shown by examining the rate
of premature convergence during the run. Ripple
crossover produces populations whose fitness increases
gradually over time, slower than, but to an eventual
higher level than that of sub-tree crossover.
%0 Conference Paper
%1 keijzer:2001:EuroGP
%A Keijzer, Maarten
%A Ryan, Conor
%A O'Neill, Michael
%A Cattolico, Mike
%A Babovic, Vladan
%B Genetic Programming, Proceedings of EuroGP'2001
%C Lake Como, Italy
%D 2001
%E Miller, Julian F.
%E Tomassini, Marco
%E Lanzi, Pier Luca
%E Ryan, Conor
%E Tettamanzi, Andrea G. B.
%E Langdon, William B.
%I Springer-Verlag
%K Context Crossover, Free Grammars, Intrinsic Polymorphism algorithms, evolution, genetic grammatical programming,
%P 74--86
%T Ripple Crossover in Genetic Programming
%U http://www.springerlink.com/openurl.asp?genre=article&issn=0302-9743&volume=2038&spage=74
%V 2038
%X This paper isolates and identifies the effects of the
crossover operator used in Grammatical Evolution. This
crossover operator has already been shown to be adept
at combining useful building blocks and to outperform
engineered crossover operators such as Homologous
Crossover. This crossover operator, Ripple Crossover is
described in terms of Genetic Programming and applied
to two benchmark problems.
Its performance is compared with that of traditional
sub-tree crossover on populations employing the
standard functions and terminal set, but also against
populations of individuals that encode Context Free
Grammars. Ripple crossover is more effective in
exploring the search space of possible programs than
sub-tree crossover. This is shown by examining the rate
of premature convergence during the run. Ripple
crossover produces populations whose fitness increases
gradually over time, slower than, but to an eventual
higher level than that of sub-tree crossover.
%@ 3-540-41899-7
@inproceedings{keijzer:2001:EuroGP,
abstract = {This paper isolates and identifies the effects of the
crossover operator used in Grammatical Evolution. This
crossover operator has already been shown to be adept
at combining useful building blocks and to outperform
engineered crossover operators such as Homologous
Crossover. This crossover operator, Ripple Crossover is
described in terms of Genetic Programming and applied
to two benchmark problems.
Its performance is compared with that of traditional
sub-tree crossover on populations employing the
standard functions and terminal set, but also against
populations of individuals that encode Context Free
Grammars. Ripple crossover is more effective in
exploring the search space of possible programs than
sub-tree crossover. This is shown by examining the rate
of premature convergence during the run. Ripple
crossover produces populations whose fitness increases
gradually over time, slower than, but to an eventual
higher level than that of sub-tree crossover.},
added-at = {2008-06-19T17:35:00.000+0200},
address = {Lake Como, Italy},
author = {Keijzer, Maarten and Ryan, Conor and O'Neill, Michael and Cattolico, Mike and Babovic, Vladan},
biburl = {https://www.bibsonomy.org/bibtex/2c489bddd17014c07342a23120f128c85/brazovayeye},
booktitle = {Genetic Programming, Proceedings of EuroGP'2001},
editor = {Miller, Julian F. and Tomassini, Marco and Lanzi, Pier Luca and Ryan, Conor and Tettamanzi, Andrea G. B. and Langdon, William B.},
interhash = {e5d7fa403c42d3b8f640d3828a11a0a5},
intrahash = {c489bddd17014c07342a23120f128c85},
isbn = {3-540-41899-7},
keywords = {Context Crossover, Free Grammars, Intrinsic Polymorphism algorithms, evolution, genetic grammatical programming,},
month = {18-20 April},
notes = {EuroGP'2001, part of \cite{miller:2001:gp}},
organisation = {EvoNET},
pages = {74--86},
publisher = {Springer-Verlag},
publisher_address = {Berlin},
series = {LNCS},
size = {13 pages},
timestamp = {2008-06-19T17:43:02.000+0200},
title = {Ripple Crossover in Genetic Programming},
url = {http://www.springerlink.com/openurl.asp?genre=article&issn=0302-9743&volume=2038&spage=74},
volume = 2038,
year = 2001
}