A Divide and Conquer strategy for improving efficiency and probability of success in Genetic Programming
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gp-bibliography.bib Revision:1.8081
- @InProceedings{eurogp06:FillonBartoli,
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author = "Cyril Fillon and Alberto Bartoli",
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title = "A Divide and Conquer strategy for improving efficiency
and probability of success in Genetic Programming",
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editor = "Pierre Collet and Marco Tomassini and Marc Ebner and
Steven Gustafson and Anik\'o Ek\'art",
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booktitle = "Proceedings of the 9th European Conference on Genetic
Programming",
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publisher = "Springer",
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series = "Lecture Notes in Computer Science",
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volume = "3905",
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year = "2006",
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address = "Budapest, Hungary",
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month = "10 - 12 " # apr,
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organisation = "EvoNet",
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keywords = "genetic algorithms, genetic programming",
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ISBN = "3-540-33143-3",
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pages = "13--23",
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email = "cfillon@units.it",
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DOI = "doi:10.1007/11729976_2",
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bibsource = "DBLP, http://dblp.uni-trier.de",
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abstract = "A common method for improving a genetic programming
search on difficult problems is either multiplying the
number of runs or increasing the population size. We
propose a new search strategy which attempts to obtain
a higher probability of success with smaller amounts of
computational resources. We call this model Divide &
Conquer since our algorithm initially partitions the
search space in smaller regions that are explored
independently of each other. Then, our algorithm
collects the most competitive individuals found in each
partition and exploits them in order to get a solution.
We benchmarked our proposal on three problem domains
widely used in the literature. Our results show a
significant improvement of the likelihood of success
while requiring less computational resources than the
standard algorithm.",
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notes = "Part of \cite{collet:2006:GP} EuroGP'2006 held in
conjunction with EvoCOP2006 and EvoWorkshops2006",
- }
Genetic Programming entries for
Cyril Fillon
Alberto Bartoli
Citations