EC-KitY: Evolutionary computation tool kit in Python with seamless machine learning integration

Moshe Sipper; Tomer Halperin; Itai Tzruia; Achiya Elyasaf

doi:10.1016/j.softx.2023.101381

EC-KitY: Evolutionary computation tool kit in Python with seamless machine learning integration

Moshe Sipper
, Tomer Halperin
, Itai Tzruia
, Achiya Elyasaf

Research output: Contribution to journal › Article › peer-review

14 Scopus citations

Abstract

EC-KitY is a comprehensive Python library for doing evolutionary computation (EC), licensed under the BSD 3-Clause License, 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.

Original language	English
Article number	101381
Journal	SoftwareX
Volume	22
DOIs	https://doi.org/10.1016/j.softx.2023.101381
State	Published - 1 May 2023

Keywords

Evolutionary algorithms
Evolutionary computation
Genetic programming
Machine learning
Scikit-learn

ASJC Scopus subject areas

Software
Computer Science Applications

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10.1016/j.softx.2023.101381

Cite this

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title = "EC-KitY: Evolutionary computation tool kit in Python with seamless machine learning integration",

abstract = "EC-KitY is a comprehensive Python library for doing evolutionary computation (EC), licensed under the BSD 3-Clause License, 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.",

keywords = "Evolutionary algorithms, Evolutionary computation, Genetic programming, Machine learning, Scikit-learn",

author = "Moshe Sipper and Tomer Halperin and Itai Tzruia and Achiya Elyasaf",

note = "Publisher Copyright: {\textcopyright} 2023 The Author(s)",

year = "2023",

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doi = "10.1016/j.softx.2023.101381",

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AU - Sipper, Moshe

AU - Halperin, Tomer

AU - Tzruia, Itai

AU - Elyasaf, Achiya

PY - 2023/5/1

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AB - EC-KitY is a comprehensive Python library for doing evolutionary computation (EC), licensed under the BSD 3-Clause License, 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.

KW - Evolutionary algorithms

KW - Evolutionary computation

KW - Genetic programming

KW - Machine learning

KW - Scikit-learn

UR - https://www.scopus.com/pages/publications/85152034371

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JO - SoftwareX

JF - SoftwareX

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ER -

EC-KitY: Evolutionary computation tool kit in Python with seamless machine learning integration

Abstract

Keywords

ASJC Scopus subject areas

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