#learning #radiate #evolution #artificial #genetic

radiate

A Rust library for genetic algorithms and artificial evolution

39 stable releases

Uses new Rust 2024

1.2.12 May 11, 2025
1.2.10 Apr 10, 2025
1.2.9 Mar 10, 2025
1.2.6 Dec 15, 2024
1.0.3 Nov 22, 2019

#29 in Simulation

Download history 151/week @ 2025-02-05 80/week @ 2025-02-12 2/week @ 2025-02-19 7/week @ 2025-02-26 91/week @ 2025-03-05 41/week @ 2025-03-12 4/week @ 2025-03-19 134/week @ 2025-04-09 16/week @ 2025-04-16 8/week @ 2025-04-23 2/week @ 2025-04-30 273/week @ 2025-05-07 49/week @ 2025-05-14

335 downloads per month
Used in 3 crates

MIT license

390KB
9K SLoC

Radiate

master branch checks Crates.io pypi.org License Static badge

For more details check radiate's website or cargo docs.

As of 05/09/2025 Python bindings are in active development.

Radiate is a powerful Rust library designed for implementing genetic algorithms and artificial evolution techniques. It provides a fast and flexible framework for creating, evolving, and optimizing solutions to complex problems using principles inspired by natural selection and genetics. With an intuitive, 'plug and play' style API, Radiate allows you to quickly test a multitude of evolutionary strategies and configurations.

  • Traditional genetic algorithm implementation.
  • Single & Multi-objective optimization support.
  • Neuroevolution (graph-based representation - evolving neural networks) support. Simmilar to NEAT.
  • Genetic programming support (tree-based representation)
  • Built-in support for parallelism.
  • Extensive selection, crossover, and mutation operators with the ability to create custom ones.

Dependencies

~0.6–1MB
~22K SLoC