  A recently proposed class of machine-learning interatomic potentials ---
Moment tensor potentials (MTPs) --- is investigated in this work. MTPs are able
to actively select configurations and parametrize the potential on-the-fly. It
is shown that MTPs accurately reproduce energies, forces and stresses
calculated ab initio. As a more comprehensive test, MTPs are employed to
calculate vacancy diffusion rates in Al, Mo and Si. We demonstrate that the
results are in a good agreement with ab initio data for the materials
considered.
