CMA Evolution Strategy

does this and that…

class olympus.planners.Cma(*args, **kwargs)[source]

Covariance Matrix Adaptation Evolution Strategy (CMA-ES) planner.

Parameters

  • goal (str) – The optimization goal, either ‘minimize’ or ‘maximize’. Default is ‘minimize’.

  • stddev (float) – Initial standard deviation.

  • init_guess (array, optional) – initial guess for the optimization

  • init_guess_method (str) – method to construct initial guesses if init_guess is not provided. Choose from: random

  • init_guess_seed (str) – random seed for init_guess_method

Methods

tell([observations])

Provide the planner with all previous observations.

ask([return_as])

suggest new set of parameters

recommend([observations, return_as])

Consecutively executes tell and ask: tell the planner about all previous observations, and ask about the next query point.

optimize(emulator[, num_iter, verbose])

Optimizes a surface for a fixed number of iterations.