Python library for CMA Evolution Strategy.
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Updated
Jun 3, 2024 - Python
Python library for CMA Evolution Strategy.
A bare-bones Python library for quality diversity optimization.
Derivative-Free Global Optimization Method (C++, Python binding)
Official implementation of the MM'21 paper "Constrained Graphic Layout Generation via Latent Optimization" (LayoutGAN++, CLG-LO, and Layout evaluation)
Distributed implementation of popular evolutionary methods
Yarpiz Evolutionary Algorithms Toolbox for MATLAB
(GECCO 2022) CMA-ES with Margin: Lower-Bounding Marginal Probability for Mixed-Integer Black-Box Optimization
Official implementation of "Approximating Gradients for Differentiable Quality Diversity in Reinforcement Learning"
(CEC2022) Fast Moving Natural Evolution Strategy for High-Dimensional Problems
Genetic algorithms and CMA-ES (covariance matrix adaptation evolution strategy) for efficient feature selection
Covariance Matrix Adaptation Evolution Strategy (CMA-ES) implementation on C#
Deep learning and evolutionary algorithms for identification of aerodynamic parameters
CMA-ES in MATLAB
A new version of world models using Echo-state networks and random weight-fixed CNNs
A universal supervisor controller and ER suite for Webots that can be adapted to any wheeled robot morphology with ease. The project is also setup to allow for easy Reinforcement Learning experimentation with some select algorithms (CMA-ES, Novlty Search, MAP-Elites) and neural networks (fixed and recurrent).
Reproduce the results of "Neuroevolution of Self-Interpretable Agents" paper
Machine Learning Attack on Majority Based Arbiter Physical Unclonable Functions (PUFs)
MoRIS (Model of Routes of Invasive Spread). A simulator of human-mediated dispersal via transportation networks.
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