There are 0 repository under cmaes topic.
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
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.
CMA-ES in MATLAB
Course on computational design, non-linear optimization, and dynamics of soft systems at UIUC.
StochOPy WebApp is hosted online at
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
Self-Interpretable Agent implemented on the Procgen game 'Dodgeball'.
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"
This repository contains an improvement for any covariance-matix-adaptation-like evolution strategy exploiting gradient or its estimation
Three implemented evolutionary strategies using DEAP to optimize energy scheduling tasks.
All code for the results and figures shown in the report for the course AE4350.
ESKit is a portable library written in C, that provides implementations of some self-adaptive evolution strategies