DOI: 10.7256/2454-0757.2024.4.70462

Abstract: The article investigates the possibility of formation of creative competencies of students within the framework of scientific personnel training. It is noted that the available training courses within the framework of general training of scientific personnel allow to prepare a specialist who is able to use existing knowledge, but such a specialist is not trained in creativity. For the formation of creative competences it is necessary to take a training course of the general theory of systems, the purpose of which is to create a universal methodology of reliable representation of models of objects, based on the similarity (isomorphism) of the forms and laws of the universe. A detailed argumentation of the connection between creativity and holistic representation of being, the empirical manifestation of which is isomorphism, is given. The mechanism of knowledge translation within the framework of the mechanism of multisystem integration of human being, the mechanism of knowledge borrowing by human being from sensually comprehended forms of reality is investigated. It is stated that in order to meet the set tasks of cognition, a version of the general theory of systems, extended by the metaphysical component, is required. Further, starting from the metaphysical description of the foundations of the phenomenon of isomorphism observed in the practice of cognition, it is possible to form complete collections of patterns – typical forms, templates of objects and their relations. At present, the work on such a version of the general theory of systems is being finalized. The article concludes with a discussion of the problematics of teaching general systems theory. It emphasizes two components: the issue of positioning the training course "General Theory of Systems" in relation to other courses, as well as taking into account the specifics of the subject area of students in different specialties (directions).

DOI: 10.25136/2409-8728.2024.1.69254

Abstract: The article is devoted to the study of the problem of increasing the reliability of modeling of cognitive systems, to which the authors refer not only human intelligence, but also artificial intelligence systems, as well as intelligent control systems for production, technological processes and complex equipment. It is shown that the use of cognitive systems for solving control problems causes very high rapidity requirements for them. These requirements combined with the necessity to simplify modeling methods as the modeling object becomes more complex determine the choice of an approach to modeling cognitive systems. Models should be based on the use of simple algorithms in the form of trend detection, correlation, as well as (for solving intellectual problems) on the use of algorithms based on the application of various patterns of forms and laws. In addition, the models should be decentralized. An adequate representation of decentralized systems formed from a large number of autonomous elements can be formed within the framework of agent-based models. For cognitive systems, two models are the most elaborated: actor and reactor models. Actor models of cognitive systems have two possible realizations: as an instrumental model or as a simulation. Both implementations have the right to exist, but the possibilities of realizing a reliable description when using the tool model are higher, because it provides incommensurably higher rapidity, and also assumes variability of the modeled reality. The actor model can be realized by means of a large number of existing programming languages. The solution to the problem of creating simulative actor models is available in most languages that work with actors. Realization of instrumental actor models requires rapidity, which is unattainable in imperative programming. In this case, the optimal solution is to use actor metaprogramming. Such programming is realizable in many existing languages.

DOI: 10.7256/2454-0757.2023.12.69095

Abstract: The article is devoted to the study of the nature of consciousness within the framework of the information concept. The paper proposes a definition of consciousness as an informational environment in which an extended model of reality is realized. The process of realization of this extended model is defined as thinking. The result of thinking is information objects that form a system in the form of information environment. Information objects are reflections of the real world properties, not directly, but by means of translation through a special object – a carrier of consciousness. In the case of human consciousness, such a carrier is a human being (represented in the form of his nervous system). As a result, consciousness can be qualified as a simulacrum of reality, i.e., a model of a model: an information model of the carrier of consciousness, which in turn is a means of physical modeling of the real "big" world. Possible mechanisms mediating thinking are considered. For this purpose, two new concepts are introduced: neural circuit and neurophysical pattern. An approach to the study of self-consciousness based on the localization of the consciousness carrier in the multidimensional space of states of initial real objects, as well as their reflections in the form of information objects is proposed. This localization is ensured by the presence of feedbacks. Summarizing the results of the study, the article states the following connection between consciousness, self-consciousness and subjectness: under certain conditions (when consciousness is localized in the state space of the carrier of consciousness), consciousness acquires the property of self-consciousness, a special case of which (when the initiator of changes determining localization is the carrier of consciousness) is self-consciousness endowed with subjectness.

DOI: 10.7256/2454-0757.2023.11.68986

Abstract: The article analyzes the possibilities and limitations of artificial intelligence. The article considers the subjectivity of artificial intelligence, determines its necessity for solving intellectual problems depending on the possibility of representing the real world as a deterministic system. Methodological limitations of artificial intelligence, which is based on the use of big data technologies, are stated. These limitations cause the impossibility of forming a holistic representation of the objects of cognition and the world as a whole. As a tool for deterministic description of the universe it is proposed to use empirical-metaphysical general theory of systems, which is an extension of existing general theories of systems due to ontological justification of the phenomenon of isomorphism and definition of a limited set of laws, rules, patterns and primitives of forms and relations of objects in the universe. The distinction of natural (human) and artificial intelligence is considered, including the realization of multisystem integration of intelligence in physical, biological, social and spiritual systems. A philosophically grounded approach to ensuring the evolutionary properties of artificial intelligence is formulated, based on the inclusion of non-equilibrium mechanisms through which stability is realized.