You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
This issue is intended to lay the groundwork for #274. An internal implementation of CMAES is required so that we can have direct access to the adapted covariance matrix. I'm currently planning to use pycma for this, as it has the API requirements to do what we need, and has proven to be performant on the battery problems we've encountered so far.
Motivation
Provides PyBOP with better acces to the CMA-ES attributes, including covariance and convergence information
Feature description
This issue is intended to lay the groundwork for #274. An internal implementation of CMAES is required so that we can have direct access to the adapted covariance matrix. I'm currently planning to use pycma for this, as it has the API requirements to do what we need, and has proven to be performant on the battery problems we've encountered so far.
Motivation
Provides PyBOP with better acces to the CMA-ES attributes, including covariance and convergence information
Possible implementation
Follow the groundwork laid out in #319 and #316
Additional context
No response
The text was updated successfully, but these errors were encountered: