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Russian Journal of Cybernetics, 2023 Volume 4, Issue 4, Pages 32–40 (Mi uk133)

Models of heuristic brain activity and artificial intelligence

V. M. Eskova, M. A. Filatovb, T. V. Voronyukb, I. S. Samoilenkob

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: In human cognitive processes, we encounter the generation and handling of two types of information: the objectively new and the subjectively new. The pursuit of creating artificial intelligence places a primary emphasis on the first type, the creation of objectively new information. In this context, such artificial systems can potentially serve as effective replacements for human cognitive abilities. The study delves into two novel operational modes of artificial neural networks, inspired by the functioning of the human brain. It was discovered that integrating these modes into existing neural networks enables us to simulate the heuristic functioning of the brain. As a result, these intelligent systems demonstrate proficiency in tackling challenges related to system synthesis and the identification of order parameters. Presently, these problems lack formalization in mathematics and do not possess a universally accepted solution.

Keywords: chaos, stochastics, brain cognitive effects, Eskov-Zinchenko effect.

DOI: 10.51790/2712-9942-2023-4-4-03



© Steklov Math. Inst. of RAS, 2024