The principles herein, of selecting experiments of multiple fidelities to find a material with an optimal property in a resource-efficient manner, could be adapted for active learning, 103 to efficiently build a predictor of the property of materials 104 using experiments of multiple fidelities. For this objective of reducing uncertainty in the predictor as opposed to optimization, the acquisition function must be modified to favor exploration.