ESs are still primarily used to solve optimization problems with continuous control variables, and for applications of this sort the natural representation of the control variables as an n-dimensional real-valued vector x is entirely appropriate. In addition, the representation of a solution may include (depending on the specific ES implementation being employed) up to n different variances and up to covariances of the generalized n-dimensional normal distribution with zero means and a probability density function:
where is the covariance matrix and z the vector of random variables. To ensure that the matrix is positive-definite, ES algorithm implementations usually work in terms of the equivalent rotation angles:
These variances, covariances and rotation angles are known as strategy parameters.