In this chapter, two real-life applications of the proposed MISO-AGP algorithm are presented. The first is the hyperparameter optimization of a machine learning algorithm with respect to two criteria: accuracy and fairness. This requires to extend MISO-AGP to the multi-objective setting, to achieve fairness, while working on multiple information sources allows to reduce the energy consumption of the hyperparameter optimization task. The second application is known as optimal sensor placement. In this case, MISO-AGP has been extended to deal with a combinatorial search space, since the sensors can be deployed to a prefixed set of possible locations. The amount of simulation scenarios considered in the search of the optimal solution defines the different information sources to use.