EC-KitY: Evolutionary Computation Tool Kit in Python with Seamless Machine Learning Integration
Created by W.Langdon from
gp-bibliography.bib Revision:1.8028
- @Misc{eckity2022,
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author = "Moshe Sipper and Tomer Halperin and Itai Tzruia and
Achiya Elyasaf",
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title = "{EC-KitY}: Evolutionary Computation Tool Kit in
{Python} with Seamless Machine Learning Integration",
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howpublished = "arXiv",
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year = "2022",
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volume = "abs/2207.10367",
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month = "22 " # jul,
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keywords = "genetic algorithms, genetic programming, Evolutionary
Algorithms, Evolutionary Computation, Machine Learning,
scikit-learn",
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biburl = "https://dblp.org/rec/journals/corr/abs-2207-10367.bib",
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bibsource = "dblp computer science bibliography, https://dblp.org",
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URL = "https://doi.org/10.48550/arXiv.2207.10367",
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DOI = "doi:10.48550/arXiv.2207.10367",
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code_url = "https://github.com/ec-kity/ec-kity/",
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size = "6 pages",
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abstract = "EC-KitY is a comprehensive Python library for doing
evolutionary computation (EC), licensed under GNU
General Public License v3.0, and compatible with
scikit-learn. Designed with modern software engineering
and machine learning integration in mind, EC-KitY can
support all popular EC paradigms, including genetic
algorithms, genetic programming, coevolution,
evolutionary multi-objective optimization, and more.
This paper provides an overview of the package,
including the ease of setting up an EC experiment, the
architecture, the main features, and a comparison with
other libraries.",
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notes = "Ben-Gurion University, Beer-Sheva 8410501, Israel",
- }
Genetic Programming entries for
Moshe Sipper
Tomer Halperin
Itai Tzruia
Achiya Elyasaf
Citations