R help - May 2018 - GA/SWARM Hyperparameter (HP) Optimisation for Classification based Machine Learning

Hi,
I believe that Caret uses a ?grid-serach approach. I was wondering if:
1 There are more efficient implementations for HP tuning for classification
algos?(eg XGboost, CatBoost, SVM, RF etc),?using say?GM/SWARM approaches, akin
to Google's approach AutoML for Image related Net problems?
2 This one is most probably wishful thinking, but is anyone looking at GM/SWARM
at HP tuning across models (ensemble models). eg?the best set of HP for combined
XGBoost + SVM, which accounts for the correlation/interaction of the prediction
assumptions.
BestAlex
	[[alternative HTML version deleted]]