Abstract

The article describes the author's approach to the construction of general-level artificial cognitive agents based on the so-called "semantic supervised learning", within which, in accordance with the hybrid paradigm of artificial intelligence, both machine learning methods and methods of the symbolic ap­ proach and knowledge-based systems are used ("good old-fashioned artificial intelligence"). А descrip­ tion of current proЬlems with understanding of the general meaning and context of situations in which narrow AI agents are found is presented. The definition of semantic supervised learning is given and its relationship with other machine learning methods is described. In addition, а thought experiment is presented, which shows the essence and meaning of supervised semantic learning.