EC-KitY: Evolutionary Computation Tool Kit in Python with Seamless Machine Learning Integration

TL;DR

EC-KitY is a versatile Python library that simplifies evolutionary computation experiments and seamlessly integrates with machine learning tools like scikit-learn, supporting various EC paradigms.

Contribution

This paper introduces EC-KitY, a comprehensive and modern Python library for evolutionary computation with machine learning integration, supporting multiple EC paradigms.

Findings

Supports all popular EC paradigms

Easy setup for EC experiments

Compatible with scikit-learn

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.