Abstract The quality of optimised decision-making algorithms (estimation, forecasting, classification, hypothesis testing, economic, medical or political decision-making, management, etc.) depends, often critically, on the choice of their parameters (order of models, weight of individual attributes in multi-criteria decision-making, probability of mutations in genetic algorithms, etc.). Therefore, it is desirable to set them, preferably automatically. The work focuses on a general solution to this problem, seen as decision-making in the meta-space of parameters (MSc) and testing of the existing solution (BSc).