We consider a model of a hierarchical transport corporation in which the executive and his subordinate factory manager organize two-level manufacturing. The chief of the corporation with a consultant supervises them. The executive knows the capabilities of increasing manufacturing output only at its own level. The manager knows the manufacturing potential of the factory. Neither the chief nor his consultant knows capabilities of the executive and the manager. So, the executive can manipulate his own output in order to influence the decisions of the consultant and the chief. However, the executive itself does not know the potential of the factory. Such ignorance can also be used by the manager to his own advantage. So, the executive needs to learn to control the manager. The reward functions of the executive and the manager are introduced in the model. Sufficient conditions are found for the synthesis of a hierarchy of controllers, which ensure the use of random opportunities for increasing output. In these conditions, the chief needs consultations with the help of a self-learning consultant. Through these consultations, the chief can norm the executive's output. The Learning controller encourages the executive, firstly, to maximize auxiliary output and, secondly, to implement an adaptive controller for the manager. Such an adaptive controller includes planning and incentive procedures that encourage the manager to maximize the manufacturing in the factory. The developed approach is illustrated by an example from the practice of a car repair corporation.