plot.OptState() now supports multiple categorical
variables.crit.aei works with wrapped learners.mbo() can be called without control object.plot(opt.state) now also works for Param Sets
with transformations.progress argument. Termination criterions now can supply a
progress return value.save.on.disk now can take arbitrary numeric vectors to
specify iterations, when to save on disk.makeMBOControl() has on.surrogate.error
argument which enables random proposals if the surrogate model
fails.initSMBO(), updateSMBO() and
finalizeSMBO() it is now possible to do a human-in-the-loop
MBO.final.opt.state.OptState objects.citation("mlrMBO").
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