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*.