Loop functions determine the behavior of the Bayesian Optimization algorithm on a global level.
For an overview of readily available loop functions, see as.data.table(mlr_loop_functions).
In general, a loop function is simply a decorated member of the S3 class loop_function.
Attributes must include: id (id of the loop function), label (brief description), instance ("single-crit" and
or "multi_crit"), and man (link to the manual page).
As an example, see, e.g., bayesopt_ego.