Novelty-based Fitness: An Evaluation under the Santa Fe Trail
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @InProceedings{Doucette:2010:EuroGP,
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author = "John Doucette and Malcolm Heywood",
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title = "Novelty-based Fitness: An Evaluation under the Santa
Fe Trail",
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booktitle = "Proceedings of the 13th European Conference on Genetic
Programming, EuroGP 2010",
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year = "2010",
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editor = "Anna Isabel Esparcia-Alcazar and Aniko Ekart and
Sara Silva and Stephen Dignum and A. Sima Uyar",
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volume = "6021",
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series = "LNCS",
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pages = "50--61",
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address = "Istanbul",
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month = "7-9 " # apr,
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organisation = "EvoStar",
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "978-3-642-12147-0",
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DOI = "doi:10.1007/978-3-642-12148-7_5",
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abstract = "We present an empirical analysis of the effects of
incorporating novelty-based fitness (phenotypic
behavioral diversity) into Genetic Programming with
respect to training, test and generalization
performance. Three novelty-based approaches are
considered: novelty comparison against a finite archive
of behavioral archetypes, novelty comparison against
all previously seen behaviors, and a simple linear
combination of the first method with a standard fitness
measure. Performance is evaluated on the Santa Fe
Trail, a well known GP benchmark selected for its
deceptiveness and established generalization test
procedures. Results are compared to a standard
quality-based fitness function (count of food eaten).
Ultimately, the quality style objective provided better
overall performance, however, solutions identified
under novelty based fitness functions generally
provided much better test performance than their
corresponding training performance. This is interpreted
as representing a requirement for layered learning/
symbiosis when assuming novelty based fitness functions
in order to more quickly achieve the integration of
diverse behaviors into a single cohesive strategy.",
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notes = "Part of \cite{Esparcia-Alcazar:2010:GP} EuroGP'2010
held in conjunction with EvoCOP2010 EvoBIO2010 and
EvoApplications2010",
- }
Genetic Programming entries for
John Doucette
Malcolm Heywood
Citations