Editing Inductive logic programming (section)

=== Parameter Learning ===
Parameter learning for languages following the distribution semantics has been performed by using an [[expectation-maximisation algorithm]] or by [[gradient descent]].
An expectation-maximisation algorithm consists of a cycle in which the steps of expectation and maximization are repeatedly performed. In the expectation step, the distribution of the hidden variables is computed according to the current values of the probability parameters, while in the maximisation step, the new values of the parameters are computed. 
Gradient descent methods compute the gradient of the target function and iteratively modify the parameters moving in the direction of the gradient.<ref name="pilp" />