Evolutionary Algorithms
Showing 23 of 23 projects
A Python framework for rapid prototyping and testing of evolutionary algorithms, including genetic algorithms, genetic programming, and evolution strategies.
A Python framework for rapid prototyping and testing of evolutionary algorithms, including genetic algorithms, genetic programming, and evolution strategies.
PyGAD is a Python library for building genetic algorithms and optimizing machine learning models with Keras and PyTorch support.
A scalable, hardware-accelerated neuroevolution toolkit built on JAX for parallel training across TPUs/GPUs.
An evolutionary optimization library for Go implementing genetic algorithms, particle swarm optimization, differential evolution, and other algorithms.
A JAX-based library providing accelerated reinforcement learning environments with full compatibility to the classic gym API.
A scikit-learn compatible hyperparameter optimization tool using evolutionary algorithms instead of grid search.
A Python framework for multiobjective evolutionary algorithms (MOEAs) with support for NSGA-II, NSGA-III, MOEA/D, and other optimization methods.
A hardware-accelerated Python library for running Quality-Diversity and neuroevolution algorithms in minutes instead of days.
A decentralized hyperparameter optimization framework for Go, inspired by Optuna, supporting Bayesian optimization and evolution strategies.
A Python library for feature selection using nature-inspired wrapper algorithms like particle swarm, grey wolf, and genetic optimization.
A fast and flexible Rust library for implementing genetic algorithms, neuroevolution, and genetic programming.
An artificial life simulation system that evolves neural networks for artificial intelligence research.
A flexible Rust framework for building and running genetic algorithm simulations for optimization and search problems.
A neuroevolution-based trading bot that evolves populations of neural networks to trade cryptocurrency using technical analysis.
A genetic programming platform for Python with TensorFlow for fast CPU and GPU symbolic regression and classification.
A Rust library for writing evolutionary algorithms to solve optimization problems like TSP, Sudoku, and OCR.
A collection of neuroevolution experiments for reinforcement learning control problems using unsupervised learning feature extractors.
A strongly-typed genetic programming framework for Python that makes evolutionary algorithms accessible and fun.
A machine learning and optimization framework for Objective-C and Swift, focused on regression and multi-objective evolutionary algorithms.
A genetic programming library for Clojure that evolves programs using mutation, reproduction, and fitness functions.
A Java library of customizable, hybridizable, iterative, parallel, stochastic, and self-adaptive local search algorithms.
A Common Lisp library implementing evolutionary algorithms including Genetic Programming and Differential Evolution for optimization tasks.
Related Tags
Found a gem we're missing?
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.