CMA-ES has two hyperparameters: the initial standard deviation for each feature of the COF representation and the number of new candidate COFs acquired in each iteration (the population size). We initialized the CMA-ES algorithm with a randomly selected COF and set the initial standard deviation to . to cover our COF feature space [0, 1] 12 . The population size, , was determined by a default heuristic in the cma library in Python.