New mboContinue needed to allow changing strategies mid-stream

[zkurtz]

If I understand the current mboContinue function correctly, it only allows you to finish a previously defined run according to some initial control settings. How hard would it be to generalize this to allow continuation (building on old results) while switching to a search strategy (new control object and/or new learner)? Here is a sketch of such a function, but it of course won't run as is:

#' @description continue search, building on previous run, but this time 
#' according to [potentially new and modified] learner and control  arguments
mbo_continue = function(run, objective, new_lrn, new_ctrl){
    history = as.data.frame(run$opt.path)
    new_run = mlrMBO::mbo(run
                          control = new_ctrl, 
                          learners = new_lrn)
    new_history = as.data.frame(new_run$opt.path)
    new_history = new_history[new_history$dob > 0,]
    new_run$history = rbind(history, new_history)
    return(new_run)
}

To clarify, it's not hard to build a wrapper that uses old history to define a new design object with precomputed values and then start a new search. The real challenge here is building such a wrapper that preserves all history from both runs in a cohesive way.

[jakob-r]

Unfortunately it is a bit hard to do it now because of the way the history is saved. I am working heavily on related issues at the moment and I have the same things in mind.
For a more open way to acces MBO look at #397 (it even includes a vignette
You could access and modify elements of the opt.state with the $ operator. For other stuff you have to dive in deeper into the package. Therefore you could have a look at the project_coneptdrift branch which uses more flexible way to store the OptPath, so that subsetting like you have it in mind becomes more easy.