Articles | Open Access | DOI: https://doi.org/10.37547/supsci-ojhpl-05-12-79

SYNERGETIC METHODOLOGY FOR THE STUDY OF ARTIFICIAL COGNITIVE SYSTEMS

Ilhom Imomaliyevich Rizayev ,

Abstract

This article analyzes the theoretical and practical significance of synergetic methodology in studying the formation, development, and functional activity of artificial cognitive systems. The study provides scientific insights into the emergence of consciousness in the information environment and the role of evolutionary processes based on mechanisms of nonequilibrium stability, fluctuations, and self-organization in the functioning of artificial systems. It also assesses the transformative impact of artificial intelligence on management, the labor market, moral decision-making, and social development from a performance perspective. Along with the technical and informational structure of artificial cognitive systems, the article examines their impact on social and spiritual processes using a synergetic approach. The results of the study allow us to assess artificial intelligence as an important factor in national development, identify its potential and risks, and formulate scientific and methodological principles for its management.

Keywords

Artificial intelligence, artificial cognitive systems, synergetics, self-organization, fluctuation, nonequilibrium stability, information model of consciousness, control systems, labor market, moral responsibility, technical development, social transformation.

References

Султанова Г. Эпистемологическая интерпретация когнитивных систем //Общество и инновации. – 2022. – Т. 3. – №. 3/S. – С. 432-437.

Nirenburg S. Cognitive Systems as Explanatory Artificial Intelligence. In: Ga-la, N., Rapp, R., Bel-Enguix, G. (eds) Language Production, Cognition, and the Lexicon. Text, Speech and Language Technology. 2015. Vol. 48. P. 37-49.

Грибков А.А., Зеленский А.А. Общая теория систем и креативный искусственный интеллект // Философия и культура. 2023. №11. С. 32-44.

Singer W. Differences between natural and artificial cognitive systems //Robotics, AI, and Humanity: Science, Ethics, and Policy. – 2021. – С. 17-27.

Kleinberg J. et al. The inversion problem: Why algorithms should infer mental state and not just predict behavior //Perspectives on Psychological Science. – 2024. – Т. 19. – №. 5. – С. 827-838.

Seth A. K., Bayne T. Theories of consciousness //Nature reviews neuroscience. – 2022. – Т. 23. – №. 7. – С. 439-452.

Bauer E. The definition of living being based on its thermodynamic properties and the resulting basic biological principles (in German). 1920a Naturwissenschaften р. 32.

Glansdorff P., Prigogine I., Hill R. N. Thermodynamic theory of structure, stability and fluctuations //American Journal of Physics. – 1973. – Т. 41. – №. 1. – С. 147-148.

Akaev А.А., Sadovnichiy V.A. Revisited economic theory or how to describe the processes of disequilibrium and instability of modern economic systems //The Economics of Digital Transformation: Approaching Non-stable and Uncertain Digitalized Production Systems. – 2021. – С. 25-43.

Тўраев Б.О. ва бошқ. Синергетика: моҳияти, қонуниятлари ва амалиётда намоён бўлиши. Т.: Наврўз нашриёти (2017): 12-13.

Benítez‐Burraco A., Ferretti F., Progovac L. Human self‐domestication and the evolution of pragmatics. Cognitive science 45.6 (2021): e12987.

Rinaldi L., Torquati M., Mencagli G., Danelutto M., Menga T. Accelerating Actor-based Applications with Parallel Patterns // 27th Euromicro International Conference on Parallel, Distributed and Network-Based Processing. 2019. P. 140-147.

Lohstroh М., Menard С., Bateni S., Lee E. Toward a Lingua Franca for Deterministic Concurrent Systems // ACM Transactions on Embedded Computing Systems. 2021. Vol. 20. No. 4. P. 1-27.

Ушаков Д.В., Валуева Е.А. Вызовы искусственного интеллекта для психологии / Человек и системы искусственного интеллекта. Под ред. В.А. Лекторского. СПб.: Издательство «Юридический центр», 2022. С. 110.

Haken H. Principles of brain functioning: a synergetic approach to brain activity, behavior and cognition. Vol. 67. Springer Science & Business Media, 2013. р. 243–314.

Haken H. Information and self-organization: A macroscopic approach to complex systems. Springer Science & Business Media, 2006. р. 21, 36–37.

Хакен Г. Синергетика: Иерархии неустойчивостей в самоорганизующихся системах и устройствах. М.: Мир, 1985. 424 с.

Цветков В.Я. Информационная синергетика // Образовательные ресурсы и технологии. 2021. №2 (35). С. 72-78.

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Rizayev, I. I. . (2025). SYNERGETIC METHODOLOGY FOR THE STUDY OF ARTIFICIAL COGNITIVE SYSTEMS. Oriental Journal of History, Politics and Law, 5(12), 634–642. https://doi.org/10.37547/supsci-ojhpl-05-12-79