ESKit is a portable library written in C, that provides implementations of some self-adaptive evolution strategies
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Updated
May 1, 2023 - C
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.
This repository contains an improvement for any covariance-matix-adaptation-like evolution strategy exploiting gradient or its estimation
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'.
Bandit and Evolutionary Algorithms using Python
Website with interactive client-side CMA-ES (blackbox optimizer) demos. Reinforcement-learning demos allow users to control RL-trained robots.
Distributed surrogate-assisted evolutionary methods for multi-objective optimization of high-dimensional dynamical systems
StochOPy WebApp is hosted online at
Course on computational design, non-linear optimization, and dynamics of soft systems at UIUC.
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.
StochOptim provides user friendly functions to solve optimization problems using stochastic algorithms
Unity In Editor Deep Learning Tools. Using KerasSharp, TensorflowSharp, Unity MLAgent. In-Editor training and no python needed.
Python library for stochastic numerical optimization
A fully decentralized hyperparameter optimization framework
Evolutionary & genetic algorithms for Julia
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