ABSTRACTS OF ARTICLES OF THE JOURNAL "INFORMATION TECHNOLOGIES".
No. 7. Vol. 28. 2022

DOI: 10.17587/it.28.368-377

R. V. Dushkin, Chief Science and Technology Officer,
Artificial Intelligence Agency, Moscow, Russian Federation

Principles of Solving the Symbol Grounding Problem in the Development of the General Artificial Cognitive Agents

The article describes the author's approach to solving the problem of symbol grounding, which can be used in the development of artificial cognitive agents of the general level. When implementing this approach, such agents can receive the function of understanding the sense and context of the situations in which they find themselves. The article gives a brief description of the problem of understanding the meaning and sense. In addition, the author's vision is given of how the symbol grounding should occur when the artificial cognitive agent uses sensory information flows of various modality. Symbol grounding is carried out by building an associative-heterarchical network of concepts, with the help of which the hybrid architecture of an artificial cognitive agent is expanded. The novelty of the article is based on the author's approach to solving the problem, which is represented by several important principles — these are multisensory integration, the use of an associative-heterarchical network of concepts and a hybrid paradigm of artificial intelligence. The relevance of the work is based on the fact that today the problem of constructing artificial cognitive agents of a general level is becoming more and more important for solving, including within the framework of national strategies for the development of artificial intelligence in various countries of the world. The article is of a theoretical nature and will be of interest to specialists in the field of artificial intelligence, as well as to all those who want to stay within the framework of modern trends in the field of artificial intelligence.
Keywords: meaning, sense, Frege's triangle, symbol grounding, semantics, understanding, artificial intelligence, multisensory integration, associative-heterarchical network, hybrid cognitive architecture

P. 368–377

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