Generate high-quality triangulated and polygonal art from images.

High-Performance Symbolic Regression in Python and Julia

Evolutionary algorithm toolbox and framework with high performance for Python

Source code of PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).

Evolutionary multi-objective optimization platform

Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.

A 2D Unity simulation in which cars learn to navigate themselves through different courses. The cars are steered by a feedforward neural network. The weights of the network are trained using a modified genetic algorithm.

Advanced evolutionary computation library built directly on top of PyTorch, created at NNAISENSE.

🍀 Evolutionary optimization library for Go (genetic algorithm, partical swarm optimization, differential evolution)

Jenetics - Genetic Algorithm, Genetic Programming, Grammatical Evolution, Evolutionary Algorithm, and Multi-objective Optimization

A C++ platform to perform parallel computations of optimisation tasks (global and local) via the asynchronous generalized island model.

OptimLib: a lightweight C++ library of numerical optimization methods for nonlinear functions

🧬 Training the car to do self-parking using a genetic algorithm

Automated modeling and machine learning framework FEDOT

Distributed High-Performance Symbolic Regression in Julia

Streamlining reinforcement learning with RLOps. State-of-the-art RL algorithms and tools.

The first open-source AI-driven tool for automatically generating system-level test cases (also known as fuzzing) for web/enterprise applications. Currently targeting whitebox and blackbox testing of Web APIs, like REST, GraphQL and RPC (e.g., gRPC and Thrift).

The Life Engine

A Python platform to perform parallel computations of optimisation tasks (global and local) via the asynchronous generalized island model.

EvoloPy toolbox provides classical and recent nature-inspired metaheuristic for the global optimization.