cma 4.4.2

CMA-ES, Covariance Matrix Adaptation Evolution Strategy for non-linear numerical optimization in Pyt

08-09-2021 209 words One minute 0 views

Contents

CMA-ES, Covariance Matrix Adaptation Evolution Strategy for non-linear numerical optimization in Python

Stars: 1282, Watchers: 1282, Forks: 193, Open Issues: 87

The CMA-ES/pycma repo was created 9 years ago and the last code push was 3 weeks ago.
The project is very popular with an impressive 1282 github stars!

How to Install cma

You can install cma using pip

pip install cma

or add it to a project with poetry

poetry add cma

Package Details

Author: Nikolaus Hansen, Youhei Akimoto, Petr Baudis
License: None
Homepage: None
PyPi:: https://pypi.org/project/cma/
GitHub Repo:: https://github.com/CMA-ES/pycma

Classifiers

Scientific/Engineering
Scientific/Engineering/Artificial Intelligence
Scientific/Engineering/Mathematics

No cma pypi packages just yet.

Errors

A list of common cma errors.

Code Examples

Here are some cma code examples and snippets.

GitHub Issues

The cma package has 87 open issues on GitHub

Restricted sampler is very sensitive to step-size damping
Consistency warning with some constrained data sets
Convexification of the constraints in the infeasible space
Simplistic failure case for AL-CMA-ES
CMAAdaptSigmaTPA.initialize
Option to normalize principal axes in CMADataLogger.plot
[constraints_handler] poor performance observation
Code features which we could or should benchmark
'CMA_cmean' fails for extreme-ish values
Undesired CSA and TPA behavior with large population size
A function where step-size adaptation is decisive?

See more issues on GitHub