NSGA2, NSGA3, R-NSGA3, MOEAD, Genetic Algorithms (GA), Differential Evolution (DE), CMAES, PSO

lagom: A PyTorch infrastructure for rapid prototyping of reinforcement learning algorithms.

Evolutionary & genetic algorithms for Julia

A fully decentralized hyperparameter optimization framework

Python library for stochastic numerical optimization

Unity In Editor Deep Learning Tools. Using KerasSharp, TensorflowSharp, Unity MLAgent. In-Editor training and no python needed.

StochOptim provides user friendly functions to solve optimization problems using stochastic algorithms

CMA-ES in MATLAB

The official repo for GECCO 2022 paper High-Performance Evolutionary Algorithms for Online Neuronal Control in vivo and in silico

StochANNPy (STOCHAstic Artificial Neural Network for PYthon) provides user-friendly routines compatible with Scikit-Learn for stochastic learning.

Course on computational design, non-linear optimization, and dynamics of soft systems at UIUC.

StochOPy WebApp is hosted online at

Distributed surrogate-assisted evolutionary methods for multi-objective optimization of high-dimensional dynamical systems

Website with interactive client-side CMA-ES (blackbox optimizer) demos. Reinforcement-learning demos allow users to control RL-trained robots.

Bandit and Evolutionary Algorithms using Python

This github repository contains the official code for the papers, "Robustness Assessment for Adversarial Machine Learning: Problems, Solutions and a Survey of Current Neural Networks and Defenses" and "One Pixel Attack for Fooling Deep Neural Networks"

Self-Interpretable Agent implemented on the Procgen game 'Dodgeball'.

ESKit is a portable library written in C, that provides implementations of some self-adaptive evolution strategies

All code for the results and figures shown in the report for the course AE4350.

Three implemented evolutionary strategies using DEAP to optimize energy scheduling tasks.