INTUITION AND MECHANISMS OF ITS KNOWLEDGE IN THE CONTEXT OF MODERN CYBERNETICS AND THE THEORY OF COMPLEX SYSTEMS

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This article presents the fundamental foundations and specific characteristics of intuition, as well as the mechanisms for its comprehension, particularly within the framework of cybernetics and complex systems theory. Today, intuition is understood in science as a multi-level and complex phenomenon, the process of cognition of which includes both rational and irrational components. The authors convincingly argue that intuition has its own structure and a certain logic; it can be considered within the framework of nonlinear dynamics as a self-organizing system with feedback and multiple mechanisms. The analysis shows that intuitive knowledge arises where research encounters high rates of change not only in the environment but also in its component parts, incomplete empirical data, and a lack of resources. As is well known, the concept of “observer” is introduced within the paradigm of post-non-classical science, particularly within the context of the evolutionary-constructive model of scientific knowledge development. Now the observer is directly viewed as part of the system, and their intuitive decisions are perceived as the result of the interaction of internal cognitive structures with external information flows. As a result, it becomes possible to interpret intuition as a significant factor in cognition, capable of minimizing the tacitness and uncertainty of knowledge. Thus, intuition becomes a natural and objective regulator of the formation of new knowledge through the synthesis of heterogeneous information. Intuition and its mechanisms are well suited to the theory of complex systems. In particular, the phenomenon of self-organization, especially emergence in intuition, is a nonlinear interaction between system elements, resulting in transitions between different cognitive states and the formation of qualitatively new types of knowledge. Research demonstrates how and by what means parallels arise between human intuition and constructed models, how weak and implicit signals are recognized, and how intuitive probabilistic predictions are formed. Conclusion: Intuition is a unique phenomenon, a special adaptive mechanism for knowledge processing, essential for the successful functioning of humans and intelligent systems in the context of the nonequilibrium of the modern world and the increasing complexity of cognitive processes, encompassing both physical reality and the metaphysics of existence. This approach offers new prospects for the development of hybrid human-machine systems, where intuitive and rational mechanisms interact as complementary modes of cognition.