Multi-Level Grammar Genetic Programming for Scheduling in Heterogeneous Networks
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @InProceedings{Saber:2018:EuroGP,
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author = "Takfarinas Saber and David Fagan and David Lynch and
Stepan Kucera and Holger Claussen and Michael O'Neill",
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title = "Multi-Level Grammar Genetic Programming for Scheduling
in Heterogeneous Networks",
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booktitle = "EuroGP 2018: Proceedings of the 21st European
Conference on Genetic Programming",
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year = "2018",
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month = "4-6 " # apr,
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editor = "Mauro Castelli and Lukas Sekanina and
Mengjie Zhang and Stefano Cagnoni and Pablo Garcia-Sanchez",
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series = "LNCS",
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volume = "10781",
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publisher = "Springer Verlag",
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address = "Parma, Italy",
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pages = "118--134",
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organisation = "EvoStar, Species",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "978-3-319-77552-4",
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DOI = "doi:10.1007/978-3-319-77553-1_8",
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abstract = "Co-ordination of Inter-Cell Interference through
scheduling enables telecommunication companies to
better exploit their Heterogeneous Networks. However,
it requires from these entities to implement an
effective scheduling algorithm. The state-of-the-art
for the scheduling in Heterogeneous Networks is a
Grammar-Guided Genetic Programming algorithm which
evolves, from a given grammar, an expression that maps
to the scheduling of transmissions. We evaluate in our
work the possibility of improving the results obtained
by the state-of-the-art using a layered grammar
approach. We show that starting with a small restricted
grammar and introducing the full functionality after 10
generations outperforms the state-of-the-art, even when
varying the algorithm used to generate the initial
population and the maximum initial tree depth.",
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notes = "Part of \cite{Castelli:2018:GP} EuroGP'2018 held in
conjunction with EvoCOP2018, EvoMusArt2018 and
EvoApplications2018",
- }
Genetic Programming entries for
Takfarinas Saber
David Fagan
David Lynch
Stepan Kucera
Holger Claussen
Michael O'Neill
Citations