Abstract. A conceptual framework, whose goal is the improvement of efficiency of machine learning, is presented. The framework is designed in a broader context of problem solver (PS). The design is solved as an integration of all basic cognitive functions and as a software-engineering problem. Many (one hundred) requirements imposed on PS are considered. The most important of them are the object-oriented nature of the PS environment, reflexivity of PS, and central role of tool and shifted border.1