Abstract
The national strategy for the development of artificial intelligence for the period up to 2030 sets the task of a significant increase in the number of scientific articles by Russian scientists in this field. To do this, it is necessary to navigate the priorities, problems and prospects of scientific research carried out all over the world. However, there is currently not a single generalizing work on regional economic studies using artificial intelligence algorithms. Therefore, the object of the study was the world array of scientific publications on regional economic research, and the subject of the study was a lot of articles on the use of artificial intelligence algorithms in such studies. The purpose of the work was to generalize world experience. To select the necessary publications, a self-organizing semantic search algorithm has been developed, based on the ideas of content analysis, expert systems and machine learning. The search was carried out in the Scopus database. About a hundred articles were identified. A brief description of ten artificial intelligence algorithms used in regional economic research is given. Analysis of world experience has revealed five features: algorithms are not used to solve all research problems; are not aimed at creating a universal autonomous artificial intelligence system; are increasingly focusing outside of artificial neural networks; rarely used in combination; in domestic works are less diverse than in competing countries. It is proposed to focus efforts on identification of economic regions of specific functioning of production, transport and service systems of artificial intelligence; identification of territorial digital platforms; analysis of the intensity of gravitational interaction of geographically distributed socio-economic objects through 5G and 6G telecommunication networks; assessment of the direction and volume of regional information flows; determination of models of spatial diffusion of innovations in artificial intelligence among Russian regions. The accelerated development of these areas with significant government support will allow Russia to provide a methodological gap from other countries in the field of regional economic research by 2030
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