Timofieva N.K.
Artificial intelligence problems and combinatorial optimization

The method of modeling artificial intelligence problems using the theory of combinatorial optimization is described. As a result of these studies, the combinatorial nature of problems of this class was established, the cause of uncertainty of various types, which arises in the process of their solution, was revealed, and the nature of the fuzziness of the input data was explained. An example of the clustering problem is used to consider the situation of uncertainty caused by the structure of the argument (combinatorial set). © 2023, Springer Science+Business Media, LLC, part of Springer Nature.

Keywords: artificial intelligence, clustering problem, combinatorial configurations, combinatorial optimization, uncertainty situation, Artificial intelligence, Clustering problems, Combinatorial configuration, Input datas, Method of modeling, Uncertainty, Uncertainty situation, Combinatorial optimization

Cite:
Timofieva N.K. (2023). Artificial intelligence problems and combinatorial optimization. Cybernetics and Systems Analysis, 59 (4), 3–11. doi: https://doi.org/10.1007/s10559-023-00586-y http://jnas.nbuv.gov.ua/article/UJRN-0001415719 [In Ukrainian].