Designing automatically a representation for grammatical evolution
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- @Article{Medvet:GPEM,
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author = "Eric Medvet and Alberto Bartoli and
Andrea {De Lorenzo} and Fabiano Tarlao",
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title = "Designing automatically a representation for
grammatical evolution",
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journal = "Genetic Programming and Evolvable Machines",
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year = "2019",
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volume = "20",
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number = "1",
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pages = "37--65",
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month = mar,
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keywords = "genetic algorithms, genetic programming, Grammatical
evolution, Genotype-phenotype mapping, Meta-evolution",
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ISSN = "1389-2576",
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URL = "https://sites.google.com/site/machinelearningts/publications/international-journal-publications/designingautomaticallyarepresentationforgrammaticalevolution/2018-GENP-AutomaticRepresentationDesign.pdf",
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DOI = "doi:10.1007/s10710-018-9327-2",
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size = "29 pages",
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abstract = "A long-standing problem in evolutionary computation
consists in how to choose an appropriate representation
for the solutions. In this work we investigate the
feasibility of synthesizing a representation
automatically, for the large class of problems whose
solution spaces can be defined by a context-free
grammar. We propose a framework based on a form of
meta-evolution in which individuals are candidate
representations expressed with an ad hoc language that
we have developed to this purpose. Individuals compete
and evolve according to an evolutionary search aimed at
optimizing such representation properties as
redundancy, uniformity of redundancy, and locality. We
assessed experimentally three variants of our framework
on established benchmark problems and compared the
resulting representations to human-designed
representations commonly used (e.g., classical
grammatical evolution). The results are promising as
the evolved representations indeed exhibit better
properties...",
- }
Genetic Programming entries for
Eric Medvet
Alberto Bartoli
Andrea De Lorenzo
Fabiano Tarlao
Citations