Artificial Intelligence: strategies and methods for solving complex problems

The Aim is to specify the concepts of “artificial intelligence” and “complex problem”, as well as to examine the state of the art in the application of artificial intelligence in solving complex problems. Methods. The author used contextual search, system analysis, and generalisation of information. Results. The paper identifies the key obstacle preventing the application of artificial intelligence in solving complex problems that consists in the lack of a conceptual and technical solution to present interdisciplinary knowledge in a form that could be processed and synthesised using artificial intelligence. Computer training that uses a variety of data sets, but does not involve an understanding of the synthesis process that the human brain so easily deals with, prohibits artificial intelligence from discovering something new, fundamentally unknown, which is imperative for solving complex problems. A common language is required that would simulate the processes of human thinking. Conclusion. The analysis and recommendations presented in this paper allow looking at the problem of artificial intelligence application as part of solving complex problems from a point of view that is different from the currently common focus on the use of fast search algorithms (the so-called large language models). The creation of a translator language between different fields of knowledge should contribute to an interdisciplinary exchange, the development of creative thinking, the emergence of new ideas and innovative solutions in various fields of human activity. An elaborate language will allow solving complex problems by combining various disciplines.