#learning #radiate #artificial #evolution #genetic

radiate-selectors

Selection strategies for the Radiate genetic algorithm library

2 stable releases

Uses new Rust 2024

new 1.2.12 May 11, 2025
1.2.11 May 9, 2025

#135 in Simulation

Download history 82/week @ 2025-05-04

82 downloads per month
Used in 5 crates (2 directly)

MIT license

240KB
6K SLoC

Radiate

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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

~405KB