NEAT, There's No Bloat
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @InProceedings{trujillo:2014:EuroGP,
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author = "Leonardo Trujillo and Luis Munoz and
Enrique Naredo and Yuliana Martinez",
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title = "NEAT, There's No Bloat",
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booktitle = "17th European Conference on Genetic Programming",
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year = "2014",
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editor = "Miguel Nicolau and Krzysztof Krawiec and
Malcolm I. Heywood and Mauro Castelli and Pablo Garcia-Sanchez and
Juan J. Merelo and Victor M. {Rivas Santos} and
Kevin Sim",
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series = "LNCS",
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volume = "8599",
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publisher = "Springer",
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pages = "174--185",
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address = "Granada, Spain",
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month = "23-25 " # apr,
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organisation = "EvoStar",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "978-3-662-44302-6",
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DOI = "doi:10.1007/978-3-662-44303-3_15",
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abstract = "The Operator Equalisation (OE) family of bloat control
methods have achieved promising results in many
domains. In particular, the Flat-OE method, that
promotes a flat distribution of program sizes, is one
of the simplest OE methods and achieves some of the
best results. However, Flat-OE, like all OE variants,
can be computationally expensive. This work proposes a
simplified strategy for bloat control based on Flat-OE.
In particular, bloat is studied in the NeuroEvolution
of Augmenting Topologies (NEAT) algorithm. NEAT
includes a very simple diversity preservation technique
based on speciation and fitness sharing, and it is
suggested that with some minor tuning, speciation in
NEAT can promote a flat distribution of program size.
Results indicate that this is the case in two benchmark
problems, in accordance with results for Flat-OE. In
conclusion, NEAT provides a worthwhile strategy that
could be extrapolated to other GP systems, for
effective and simple bloat control.",
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notes = "Part of \cite{Nicolau:2014:GP} EuroGP'2014 held in
conjunction with EvoCOP2014, EvoBIO2014, EvoMusArt2014
and EvoApplications2014",
- }
Genetic Programming entries for
Leonardo Trujillo
Luis Munoz Delgado
Enrique Naredo
Yuliana Martinez
Citations