Abstract
Modern autonomous intelligent systems must be able to independently develop their perception, interpretation, actions; to work together with people and individually; to communicate with other systems. Nowadays, they are only capable of uncontrolled learning and do not have the self-sufficient behavior feature that guarantees the fulfillment of a certain mission, particularly as a part of a human-machine system. Due to this fact, we have to revise the logical and mathematical abstractions underlying the construction of their control systems. The paper proves an approach to developing software for intelligent control systems for autonomous systems based on the theory of patterns. It is shown that the choice under heavy time pressures is based on behavioral patterns that reflect effective experience. Patterns form both the informational structure of the representations and the set of possible representations. Assessments of subject’s satisfaction with the current situation of choice lead to changing in subject’s interests structure, and he can choose it. The paper shoves the developed formal model of the behavioral pattern and proposes an approach to solving the problem of identification and construction of pattern models. There are also the results of software solutions for identifying a behavioral pattern when using new generation training systems.
The work has been financially supported by RFBR (grant no. 17-01-00728).
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Vinogradov, G.P., Konyukhov, I.A., Prokhorov, A.A. (2022). Intelligent Control of Advanced Autonomous Systems. In: Kovalev, S., Tarassov, V., Snasel, V., Sukhanov, A. (eds) Proceedings of the Fifth International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’21). IITI 2021. Lecture Notes in Networks and Systems, vol 330. Springer, Cham. https://doi.org/10.1007/978-3-030-87178-9_32
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