Fitness Clouds and Problem Hardness in Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.7970
- @InProceedings{vanneschi:fca:gecco2004,
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author = "Leonardo Vanneschi and Manuel Clergue and
Philippe Collard and Marco Tomassini and S\'ebastien V\'erel",
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title = "Fitness Clouds and Problem Hardness in Genetic
Programming",
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booktitle = "Genetic and Evolutionary Computation -- GECCO-2004,
Part II",
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year = "2004",
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editor = "Kalyanmoy Deb and Riccardo Poli and
Wolfgang Banzhaf and Hans-Georg Beyer and Edmund Burke and
Paul Darwen and Dipankar Dasgupta and Dario Floreano and
James Foster and Mark Harman and Owen Holland and
Pier Luca Lanzi and Lee Spector and Andrea Tettamanzi and
Dirk Thierens and Andy Tyrrell",
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series = "Lecture Notes in Computer Science",
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pages = "690--701",
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address = "Seattle, WA, USA",
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publisher_address = "Heidelberg",
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month = "26-30 " # jun,
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organisation = "ISGEC",
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publisher = "Springer-Verlag",
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volume = "3103",
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ISBN = "3-540-22343-6",
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ISSN = "0302-9743",
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URL = "http://www.i3s.unice.fr/~verel/publi/gecco04-FCandPbHardnessGP.pdf",
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URL = "https://rdcu.be/dnXdl",
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DOI = "doi:10.1007/978-3-540-24855-2_76",
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DOI = "doi:10.1007/b98645",
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size = "12 pages",
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keywords = "genetic algorithms, genetic programming",
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abstract = "Abstract. This paper presents an investigation of
genetic programming fitness landscapes. We propose a
new indicator of problem hardness for tree-based
genetic programming, called negative slope coefficient,
based on the concept of fitness cloud. The negative
slope coefficient is a predictive measure, i.e. it can
be calculated without prior knowledge of the global
optima.The fitness cloud is generated via a sampling of
individuals obtained with the Metropolis-Hastings
method. The reliability of the negative slope
coefficient is tested on a set of well known and
representative genetic programming benchmarks,
comprising the binomial-3 problem, the even parity
problem and the artificial ant on the Santa Fe trail.",
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notes = "GECCO-2004 A joint meeting of the thirteenth
international conference on genetic algorithms
(ICGA-2004) and the ninth annual genetic programming
conference (GP-2004)",
- }
Genetic Programming entries for
Leonardo Vanneschi
Manuel Clergue
Philippe Collard
Marco Tomassini
Sebastien Verel
Citations