{"library":"cmaes","type":"library","category":null,"description":"cmaes is a lightweight Python library providing an implementation of the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) for numerical optimization. It offers a simple \"ask-and-tell\" interface and has expanded to include various advanced CMA-ES variants such as CatCMA, CMAwM, and COMO-CatCMAwM, catering to mixed-variable and multi-objective optimization problems. The library is actively maintained, currently at version 0.13.0, with frequent updates introducing new algorithms and features.","language":"python","status":"active","version":"0.13.0","tags":["optimization","evolutionary algorithms","CMA-ES","black-box optimization","numerical optimization","hyperparameter optimization","mixed-variable optimization","multi-objective optimization"],"last_verified":"Thu May 21","install":[{"cmd":"pip install cmaes","imports":["from cmaes import CMA","from cmaes import CatCMAwM","from cmaes import COMOCatCMAwM"]},{"cmd":"conda install -c conda-forge cmaes","imports":[]}],"homepage":null,"github":"https://github.com/CyberAgentAILab/cmaes","docs":null,"changelog":null,"pypi":"https://pypi.org/project/cmaes/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":100,"avg_install_s":3.6,"avg_import_s":0.27,"wheel_type":"wheel"},"url":"https://checklist.day/v1/registry/cmaes/compatibility"}}