  Apprentice is a tool developed for event generator tuning. It contains a
range of conceptual improvements and extensions over the tuning tool Professor.
Its core functionality remains the construction of a multivariate analytic
surrogate model to computationally expensive Monte-Carlo event generator
predictions. The surrogate model is used for numerical optimization in
chi-square minimization and likelihood evaluation. Apprentice also introduces
algorithms to automate the selection of observable weights to minimize the
effect of mis-modeling in the event generators. We illustrate our improvements
for the task of MC-generator tuning and limit setting.
