Coupling active learning and the tuning of a perceptron for surrogate modeling. How would you approach this problem ? • /r/MachineLearning

I have a simulation tool that allows me to calculate a deterministic real output y given a vector of real inputs X. This simulation runs slowly (1-10sec) but I'm able to run it through scripts. I want to make a python tool allowing me to create a surrogate model of the simulation. I plan to use a multilayer perceptron (MLP) as they theoretically can adapt to any kind of response function. I want the tool to automatically find the inputs to simulate and the optimal size of MLP to reach a given precision on the output.