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Russian Journal of Cybernetics, 2021 Volume 2, Issue 3, Pages 44–52 (Mi uk82)

This article is cited in 4 papers

Artificial intellect with artificial neural networks

V. M. Eskova, M. A. Filatovb, G. V. Gazyab, N. F. Stratanb

a Surgut Branch of Federal State Institute “Scientific Research Institute for System Analysis of the Russian Academy of Sciences”, Surgut, Russian Federation
b Surgut State University, Surgut, Russian Federation

Abstract: Currently, there is no single definition of artificial intelligence. We need a Such categorization of tasks to be solved by artificial intelligence. The paper proposes a task categorization for artificial neural networks (in terms of obtaining subjectively and objectively new information). The advantages of such neural networks (non-algorithmizable problems) are shown, and a class of systems (third type biosystems) which cannot be studied by statistical methods (and all science) is presented. To study such biosystems (with unique samples) it is suggested to use artificial neural networks able to perform system synthesis (search for order parameters). Nowadays such problems are solved by humans through heuristics, and this process cannot be modeled by the existing artificial intelligence systems.

Keywords: artificial intelligence, brain neural networks, system synthesis, the Eskov–Zinchenko effect.

DOI: 10.51790/2712-9942-2021-2-3-6



© Steklov Math. Inst. of RAS, 2024