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.

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

Code for the paper "Evolved Policy Gradients"

ecr: Evolutionary Computation in R (version 2)

A julia implementation of the CMA Evolution Strategy for derivative-free optimization of potentially non-linear, non-convex or noisy functions over continuous domains.

Paper: Challenges in High-dimensional Reinforcement Learning with Evolution Strategies

Using Cartesian Genetic Programming to find an efficient Convolutional Neural Network architecture

High performance implementation of Deep neuroevolution in pytorch using mpi4py. Intended for use on HPC clusters

A pure-Swift implementation of Covariance Matrix Adaptation Evolutionary Strategy (CMA-ES).

Workbench for practical machine learning in Ruby.

Gradient-based Covariance Matrix Adaptation Evolutionary Strategy for Real Blackbox Optimization

This github repository contains the official code for the paper, "Evolving Robust Neural Architectures to Defend from Adversarial Attacks"

A tool for developing reinforcement learning algorithms focused in stock prediction

[WIP] Python implementation of evolution strategy based on Information Geometry. This library includes CMA-ES, NES, CompactGA and PBIL.

An amateur attempt at breeding a chess-playing AI.

Tiny Genetic Algorithm in Python.

Registered Software. Official code of the published article "Automatic design of quantum feature maps". This quantum machine learning technique allows to auto-generate quantum-inspired classifiers by using multiobjetive genetic algorithms for tabular data.

The optimization field suffers from the metaphor-based “pseudo-novel” or “fancy” optimizers. Most of these cliché methods mimic animals' searching trends and possess a small contribution to the optimization process itself. Most of these cliché methods suffer from the locally efficient performance, biased verification methods on easy problems, an…

Нейронная сеть оптимизируемая с помощью генетического алгоритма. Задача агента контролируемого при помощи нейронной сети состоит в том, чтобы избегать контакта с противниками, как можно более длительное время.