What is the hallmark of the cybernetic approach. Cybernetic approach and synergetic ideas in management. Artificial neural network as a type of information model

1.1. Systems approach

1.2. Cybernetics

1.3. Synergetics

1.4. Quality management - life quality management

Practical part

Glossary

Bibliography

Introduction

The search for answers to many unresolved problems of information and management, which continue to be the subject of discussion, actualizes the task of a deeper study of the creative heritage of Norbert Wiener. The founder of cybernetics owns a number of works devoted to the philosophy and methodology of science, the role of scientific knowledge in society, the problem of the universe, the analysis of the possible consequences of the scientific and technological revolution, as well as the ethics of the scientist.

Wiener's interest in philosophical problems is not accidental: it is known that at first he was going to devote himself to philosophy, he studied at Harvard University under the guidance of J. Royce and J. Santayana, received a doctorate at the age of 18, and only then, continuing to improve his education in Europe, under Russell's influence favored mathematics. Nevertheless, Wiener in his scientific work repeatedly turned to philosophical topics both in the “pre-cybernetic” period and when developing a project for a new science “on control and communication in the animal and the machine.”

Cybernetics is the science of the general laws of control in nature, society, living organisms and machines, or the science of control, communication and information processing. The object of study is dynamic systems. The subject is information processes related to their management.

The originality of this science lies in the fact that it studies not the material composition of systems and not their structure, but the result of the work of this class of systems. In cybernetics, the concept of a "black box" was first formulated as a device that performs a certain operation on the present and past of the input potential, but for which we do not necessarily have information about the structure that ensures the performance of this operation.

Systems are studied in cybernetics by their reactions to external influences, in other words, by the functions they perform. Along with the material and structural approach, cybernetics introduced the functional approach into scientific use as another variant of the system approach in the broad sense of the word.

Cybernetic approach - the study of a system based on cybernetic principles, in particular, by identifying direct and feedback links, considering the elements of the system as some "black boxes".

The purpose of the cybernetic approach is to apply the principles, methods and technical means to achieve the most effective results of optimizing control in one sense or another. The fundamental concepts of cybernetics are: system, feedback, information.

1. Theoretical part

1.1. Systems approach

Recall the basic principles of the systems approach:

1. A system is a whole that is not a simple sum of its constituent parts. The behavior of the system is determined not by the properties of individual elements, but by the nature of their interaction and the type of connections. The consequence is that it is impossible to study and understand the system by disassembling and analyzing its constituent parts.

If we single out some of its parts from the organization, say the accounting department, the supply or sales department, none of them will be able to give the product that the system as a whole produces, and which is the result of their interaction. The same applies to knowledge - although specific people are their carriers, knowledge of an organization as a system is not a simple sum of the competencies of its employees, it is also a system property, acquires new qualities at this level and obeys other laws.

The organization establishes complex relationships and interactions both within itself and with the external environment, forms intellectual (thinking) models, on the basis of which action algorithms are developed in various situations. Determining the reason why the existing state of the system differs from the desired one, it is useless to analyze a separate structure, it is necessary to investigate the processes and intellectual models that underlie them.

2. Systems are simple and complex. The complexity of systems can be twofold - composite and dynamic.

Composite complexity is determined by the number of elements, dynamic - by the nature of their relationships. Organizations have not only composite, but also dynamic complexity, since even with a small number of elements (for example, a small number of employees), the number of options for connections and interactions between them can be huge. Each employee of the organization contacts in the process of performing his functions with a number of employees of other departments, building business ties. In addition, friendly or friendly relations can be established with some colleagues, and it is known how strongly someone's family or romantic ties shown at work can affect the entire team.

3. By influencing the system, it is impossible to obtain a local result, a change in one part will cause changes in many others associated with it, which will necessarily manifest itself in side effects.

There are many examples of side effects in staff development. Here's one of the most annoying ones. Imagine an organization that spares no expense in training its employees. The professionalism of specialists is growing to the delight of management, but their value in the labor market and attractiveness to other employers are also increasing, as well as self-esteem and job requirements. It is clear that if the increased needs of highly qualified employees cannot be satisfied in the same place, competitors will not doze off.

It is precisely because of the resistance of the system to change that it is so difficult to implement any reforms, including the introduction of new knowledge, technologies and methods of work.

1.2. Cybernetics

Cybernetics arose at the intersection of many areas of knowledge: mathematics, logic, semiotics, biology and sociology.

The generalizing nature of cybernetic ideas and methods brings the science of control, which is cybernetics, closer to philosophy.

Cybernetics itself as a science of control gives a lot to modern philosophical thinking. It allows you to more deeply reveal the mechanism of self-organization of matter, enriches the content of the category of connections, causality, allows you to study the dialectics of necessity and chance, possibility and reality in more detail. Ways are opened for the development of a "cybernetic" epistemology, which does not replace dialectical materialism with the theory of knowledge, but makes it possible to clarify, detail and deepen a number of essential problems in the light of the science of management.

Having arisen as a result of the development and mutual stimulation of a number of technical, biological and social disciplines, which in the recent past were weakly interconnected, cybernetics has penetrated into many spheres of life.

Such an unusual "biography" of cybernetics is due to a number of reasons, two of which should be singled out.

First, cybernetics has an extraordinary, synthetic character. In this regard, there are still differences in the interpretation of some of its problems and concepts.

Secondly, the fundamental ideas of cybernetics came to our country from the West, where from the very beginning they were influenced by idealism and metaphysics, and sometimes by ideology. The same thing, or almost the same thing happened to us. Thus, it becomes obvious the need to develop the philosophical foundations of cybernetics, highlighting its main provisions from the standpoint of philosophical knowledge.

The comprehension of cybernetic concepts from the position of philosophy will contribute to a more successful implementation of theoretical and practical work in this area, will create better conditions for effective work and scientific research in this area of knowledge.

It is necessary to say about the great importance of cybernetics for the construction of a scientific picture of the world. Actually the subject of cybernetics is the processes occurring in control systems, the general laws of such processes.

So, cybernetics (translated from Greek as the art of control) is the science of managing complex systems with feedback. It arose at the intersection of mathematics, engineering and neurophysiology, and it was interested in a whole class of systems, both living and non-living, in which there was a feedback mechanism. The American mathematician N. Wiener (1894-1964) is rightfully considered the founder of cybernetics, who published a book in 1948, which was called Cybernetics.

The outstanding American scientist of the 20th century, Norbert Wiener, entered the history of world science as the founder of cybernetics, a field of knowledge that, in a relatively short historical period, not only became one of the leading ones, but also significantly transformed many areas of human activity.

Wiener's book "Cybernetics", which gave the name to the corresponding science, drew the attention of readers to the fact that in a general sense it is advisable to consider the following bricks of the universe - elements, devices, systems, communications, control and information. The first three "bricks" form an arbitrary structure, the fourth characterizes its integrity, the fifth - the functions performed, and the sixth - the semantic purpose. Altogether, these bricks formed a well-proportioned building system. The published book remained a real hit for three decades, only gradually giving way to textbooks, the works of interpreters and genuine successors.

A very important result of the aftereffect of the book was the formation of model thinking in science and engineering disciplines. From now on, when considering any system, it was necessary to describe not only its composition, but also the set of states in which it can be, which made it possible in many cases to deal with acceptable adequacy only with its mathematical or physical model. This opened the way to the creation of a mathematical theory of automata, which is successfully developing to this day in a wide variety of applications, from cryptography to programming. Undoubtedly, the main result of the publication of this book was an understanding of the role of management in the system, much more diverse than simple feedback. It turned out that control determines the expediency of the system's behavior. And this, of course, depends on the information processed in the system.

Until now, Wiener's thoughts about the problems and possible social consequences of the scientific and technological revolution remain relevant.

More than four decades ago, at the very beginning of the “cybernetic era”, the scientist foresaw the informatization of society that is now acquiring a global character, predicting that in the future “the development of information exchange between man and machine, between machine and man and between machine and machine is destined to play an ever-increasing role ".

In the conditions of the changed realities of the beginning of the 21st century, the Wiener criticism of any manifestations of worldview dogmatism also requires a new reading.

Here is the definition of information given by Wiener in the book “Cybernetics and Society”: “Information is a designation of the content received from the outside world in the process of our adaptation to it and our feelings adapting to it”, this definition can hardly be called exhaustive even from the point of view of cybernetics, since it has a pronounced anthropological connotation and does not cover, for example, the area of information exchange processes between parts
computing machine.

Nevertheless, this definition is essentially close to attempts to reveal the content of the concept of “information” through the concept of “reflection”, which, from the standpoint of both cybernetics and general systems theory, can be understood as the process and result of the interaction of a complex dynamic system with the environment, leading to to a change in the state of the system or to a change in its organization, corresponding to some aspects of the reflected external influence.

Such an interpretation of the concept of “reflection” and variants of its use that do not claim to be indisputable for revealing the content of the cybernetic concepts of “information”, “communication”, “message”, do not contradict the Wiener idea of cybernetics - and as a science “about control and communication in an animal and a machine” , and as a theory of organization of complex dynamic systems.

Compared with Bell's concept, Wiener's approach to understanding the features of the "two industrial revolutions" seems to be free from internal contradictions and more logical.

A characteristic feature of the first of these, which began more than two hundred years ago and ended in the second half of the last century, Wiener calls the use of technological innovations that developed “with the exception of a significant number of isolated examples ... along the line of replacing man and animal as a source of energy by machines, without affecting in any significant other human function.”

The beginning of the scientific and technological, or “second industrial” revolution, opens the era of the use of technology, for which “the human brain serves as a kind of indicator of what automatic machinery is capable of,” in the field of human intellectual activity.

The task of substantiating the initial concepts of cybernetics, especially such as information, control, feedback, etc., requires access to a wider, philosophical field of knowledge, where the attributes of matter are considered - the general properties of motion, the laws of cognition.

The main features of cybernetics as an independent scientific field are as follows:

Cybernetics contributed to the formation of the information concept of systems representation.
Cybernetics considers systems only in dynamics.
Cybernetics practices probabilistic methods for studying the behavior of complex systems.
In cybernetics, a method of studying systems is used using the concept of a "black box", which is understood as a system in which only the input and output information of this system is available to the researcher, and the internal structure may be unknown.
A very important method of cybernetics, using the concept of a "black box", is the modeling method.

As N. Wiener wrote (using the term organism in a broad sense): “Every organism is held together by the presence of means of acquiring, using, storing and transmitting information.” In the same place, he noted that "the community extends only to the extent to which the actual transmission of information extends."

The term information is also ambiguous because two types of information are distinguished. The first type is related or structural information that characterizes the organization and orderliness of the management system itself. The second type is free, relative information, information-message; It is this understanding of information that is most common in science. The volume and perception of such information depends on the preparation of the control system for its use, i.e. on the composition and volume of related information available in the system. The result of the interaction of free and related information in the control system is up-to-date information. At the same time, the process of transformation of free information into bound information is constantly taking place.

The informational approach to management processes is the first feature of cybernetics. In the information interpretation of the cybernetic approach, management in organizational systems is considered, first of all, as a process of information transformation: information about the control object is perceived by the control system, processed in accordance with a particular control goal, and transmitted to the control object in the form of control actions. Therefore, the concept of information is one of the most fundamental concepts of cybernetics. In the information interpretation, the processes of cybernetic control are associated with the receipt, transmission, processing and use of information. The processes of obtaining information, its storage and transmission in this case are identified with the concept of "communication".

The processing of the perceived information into signals that direct the activity in the object is identified with the concept of control.

If systems are able to perceive and use information about the results of their functioning, then they say that they have feedback. The processing of information coming through feedback channels into signals that correct the activity of the system is called regulation. There is a difference between the terms "management" and "regulation": if we consider that management means the impact on the results of the system to achieve the intended goal, then regulation means the type of management based on the method of equalizing deviations from the norm (standard, given value). Devices (or organs) serving this purpose are called regulators.

Phenomena that are displayed in such fundamental concepts of cybernetics as information and control take place in organic nature and social life. Thus, cybernetics can be defined as the science of control and communication with wildlife in society and technology.

One of the most important questions around which philosophical discussions are going is the question of what is information, what is its nature? To characterize the nature of information processes, it is necessary to briefly consider the natural basis of any information, and such a natural basis of information is the objective property of reflection inherent in matter.

The position on the inseparable connection between information and reflection has become one of the most important in the study of information and information processes and is recognized by the absolute majority of Russian philosophers.

Information in wildlife, unlike inanimate nature, plays an active role, as it participates in the management of all life processes.

The materialistic theory of reflection sees the solution of new problems of science and, in particular, such a cardinal problem of natural science as the transition from inorganic to organic matter, in the use of the methodological basis of dialectical materialism. The problem is that there is matter that is capable of feeling, and matter created from the same atoms and at the same time does not have this ability. The question is thus posed quite concretely and thus pushes the problem towards a solution.

Cybernetics came to grips with the study of the mechanisms of self-regulation and self-government. At the same time, while remaining methodologically limited, these achievements left open a number of problems, which were brought to the consideration of the internal breakdown of cybernetics.

Consciousness is not so much a product of the development of nature as a product of human social life, the social labor of previous generations of people. It is an essential part of human activity, through which human nature is created and cannot be accepted outside of this nature.

If in machines and in general in inorganic nature reflection is a passive, dead physical-chemical, mechanical act without generalization and penetration into the essence of the generalized phenomenon, then there is reflection in the form of consciousness, then according to F. Engels "knowledge of itself by highly organized matter, penetration into the essence , the law of development of nature, objects and phenomena of the objective world".

In a machine, reflection is not conscious, since it is carried out without the formation of ideal images and concepts, but occurs in the form of electrical impulses, signals, etc. Since the machine does not think, this is not the form of reflection that takes place in the process of human cognition of the surrounding world. The patterns of the process of reflection in a machine are determined, first of all, by the patterns of reflection of reality in the mind of a person, since a person creates a machine in order to more accurately reflect reality, and it is not the machine itself that reflects reality, but the person reflects it with the help of a machine. Therefore, the reflection of reality by a machine is an integral element of the reflection of reality by a person. The appearance of cybernetic devices does not lead to the emergence of a new form of reflection, but a new link that mediates the reflection of nature by man.

That is why information can be considered useless in the absence of feedback. In his book "Cybernetics and Society" Wiener writes: "feedback is a method of controlling a system by including in it the results that precede the performance of its tasks."

The shorter the information chain, the less likely it is to misunderstand the control signal. Because, according to Wiener, "any transmission of signals (or external interference in them) reduces the amount of information contained in them."

From a cybernetic point of view, semantically meaningful information is information passing through the transmission line plus a filter, and not information passing only through the transmission line.

The filter in this case is "the last mechanism that opens the generators and releases similar tasks."

1.3 Synergetics

Synergetics can be considered as the successor and successor of many sections of exact natural science, primarily (but not only) the theory of oscillations and the qualitative theory of differential equations. It was the theory of oscillations with its "international language", and later "nonlinear thinking" that became for synergetics the prototype of a science that builds models of systems of various nature, serving various fields of science. And the qualitative theory of differential equations, the beginning of which was laid in the works of Henri Poincaré, and the modern general theory of dynamical systems that grew out of it, armed synergetics with a significant part of the mathematical apparatus.

Synergetics is looking for its own specific language. Its foundations are laid, first of all, by the principles common to particular scientific theories, in addition, the principles of general scientific theories and, finally, the leading values of the synergetic worldview.

The principles of particular (object) theories naturally differ from each other due to the difference in subject areas. However, it is possible to single out that part of the principles that is the same for all theories and to designate the specifics of theories in the field of physics (and chemistry), biology, sociology, and psychology. . .

The following 4 principles of particular theories of synergetics can be distinguished:

Nonlinearity means non-preservation of additivity in the process of development of the represented systems. Any phenomenon is understood as a moment of evolution, as a process of movement across the field of development.
Instability means non-preservation of the "proximity" of the states of the system in the process of its evolution.
Openness means the recognition of the system's exchange of matter, energy, information with the environment and, consequently, the recognition of the system as consisting of elements connected by structure, and inclusion as a subsystem, an element in another whole.
Subordination means that the functioning and development of the system are determined by the processes in its subsystem ("supersystem") when a hierarchy of time scales arises. This is the principle of "self-simplification" of the system, ie, reduction of its dynamic description to a small number of order parameters.

To the described 4 principles are added principles specific to a particular object area - inanimate systems, living organisms, humans. Thus, for non-living (physical and chemical) systems, in one form or another, the principle of nonlocality (long-range interaction, correlation at a distance) is introduced, which means such an interaction between the elements of the system, which is perceived as information transfer at an infinite speed (which is primarily reminiscent of quantum mechanical inequalities J Bella For living (biological and technical systems approaching them) the biofield principle is introduced, which defines a special field that unites elements into a whole and directs the development of the organism to pre-established patterns (attractors). names, for example, as a morphogenetic field, postulated in the twenties by the Russian biologist A. G. Gurvich.

1.4. Quality of life management

In the modern world, a high quality of life of the population is considered a sign of the well-being of the state. The experience of advanced countries shows that in the development strategy of the Russian state it is advisable to focus on the concept of the quality of human life. Therefore, the focus of socio-economic development of the regions of Russia should be the question of how economic growth can contribute to a sustainable and progressive change in the parameters of people's lives.

A significant contribution to the formation and development of the scientific foundations of the quality of life was made by: S.A. Ayvazyan, V.F. Bezyazyachny, I.V. Bestuzhev-Lada, V.N. Bobkov, B.V. Boytsov, O.B. Grigorieva, A.A. Davydov, E.V. Davydova, E.I. Kapustin, V.F. Mayer, P.S. Mstislavsky, B.V. Rakitsky, N.M. Rimashevskaya, A.I. Subetto, V.I. Tolstykh and others.
Among foreign authors, contributions to the development of the problem were made by: R. Aron, D. Bell, Z. Brzezinski, J. Galbraith, G. Kahn, B. Little, A. McConnell, E. Mishan, J. Neasebit, W. Rostow, P .Samuelson, N. Smelser, A. Toynbee, A. Toffler, A. Pigou, D. Horley, J. Fourastier, and others.
The issues of quality of life management are presented in the works of: A.E. Ko-guta, V.I. Kotlyarova, SB. Naidanov, A.S. Revaikina, V.E. Rokhchin, V.M. Rut-gaiser, E.S. Sannikova, A.K. Solovyov, L.I. Timurov, ALO. Shevyakov and others.
The regional aspect of life quality management is considered in the works of: M.N. Alferova, E.G. Animitsy, V.P. Babintseva, A.A. Belova, V.K. Boch-kareva, A.A. Garmasheva, A.M. Elokhova, S.V. Zainchkovskaya, P.D. Kosinsky, G.P. Petropavlova, V.A. Sukhikh, N.M. Fedorova.

In the process of the current evolution of socio-economic views, concepts and trends, an important role is played by the doctrine of "quality of life", which has both independent significance and has a significant impact on a number of other modern concepts. The main provisions of the concept of quality of life had a significant impact on the formation and modification of such concepts as: "industrial", "post-industrial society", "zero growth", "welfare society", etc. The relationship between the concept of quality of life and the work carried out under the auspices of the so-called "Club of Rome" - an organization that is engaged in the formation of an understanding of the global world system in order to ensure the future of mankind, is clearly traced.
In the scientific world, the first mention of the quality of life appeared in the 50-60s of the 20th century, when the transition to the post-industrial stage of development began in the highly developed countries of the West, which led to public interest in the humanitarian content of economic progress.
Having arisen in the broad context of global problems of our time, the problem of quality of life was initially associated only with issues of environmental protection, human health, rising poverty, crime, and improving life in cities. However, very quickly this concept acquired new and broader meanings, while covering the most diverse aspects of human life. The quality of life has come to be regarded as a complex characteristic of the social, political, cultural, ideological, economic factors of a person's existence in society, including, in particular, such means of meeting human needs as environmental protection, ensuring the physical and moral health of society, humanizing working conditions and other social questions.

In other words, the quality of life began to be perceived as part of a certain futurological ideal, in which not the quantitative growth of material wealth comes to the fore, but the qualitative aspects of human life - health care, education, culture, recreation, working conditions, etc.
Doubts that economic growth is always a blessing were born as a result of the aggravation of crisis phenomena in the economic, social, and spiritual life of Western society; they also prompted scientists to reconsider many postulates in the concept of the development of the world economy and, in particular, human life.

For example, the American economist W. Rostow considered the quality of life as a natural stage in the development of a consumer society. In his opinion, economic growth based on scientific and technological progress must inevitably lead to an increase in the standard of living (standard of living), which, in turn, is the basis of a “new quality of life”. According to W. Rostow, the "new quality of life" is characterized by indicators in the field of health care, recreation, reduction of environmental pollution, the fight against poverty and inequality ... ".
D. Bell and 36. Brzezinski advocated the achievement of a new quality of life through the use of the latest achievements of science, the introduction of new technologies and machines, thereby reducing the burden on nature and freeing people from hazardous work. In their interpretation, the quality of life is an element of a post-industrial society, which is characterized by an improvement in the material situation, improvement in working conditions, an increase in the amount of free time, and an increase in access to the benefits of civilization: education, healthcare, culture, free communication, etc.

According to R. Aron, the quality of life is determined by the degree of development of the standard of living and is expressed as “an increase in individual income and its proportional spending on consumer goods, luxury (or close to luxury) and, in the end, even on such intangible things as household services, culture, spending free time. In essence, the quality of life, in the interpretation of R. Aron, differs from the standard of living in the structure of spending individual income, as well as in the fact that “luxury” and “intangible things” are also included in the “quality of life”. Recognizing that economic growth itself still creates the prerequisites for a deterioration in the quality of life, threatening environmental pollution. R. Aron was not in favor of stopping technical progress, but its "curbing" or a slight limitation.
The English economist T. Wager made an attempt to model the "standard" and "quality of life" using formulas. The quality of life, according to the author, includes the basic standard of living and, in addition, the quantity and quality of services for a certain time, as well as the quality of experience accumulated by people.

Wager expresses confidence that the "quality of life" will be largely determined by the quantity and quality of services, which will inevitably develop along with the rise in the standard of living and material production. However, he acknowledges that “the quality of life may be affected if the living environment is severely degraded.”

So, among the various criteria, the most common are the following: the state of the environment, the demographic situation, health care, housing, the degree of organization of leisure, etc.
Canadian scientists A. Lermer, F. Muller indicate that a high level of "quality of life" is possible when a person is provided with basic conditions: housing, environmentally friendly food, in addition, he must have access and conditions for education, medical care . They also agree that the “quality of life” is affected by the degree of environmental pollution, the state of health and the level of development of the healthcare system, crowding, and the level of crime.

The concept of human development is an alternative point of view that equates development solely with economic growth. Economic growth and consumption growth is seen not as an end in itself, but as a means to achieve human development goals. Thus, within the framework of this approach, it was possible to combine the opinion on the expediency of economic growth and the position on the need for the predominance of the qualitative aspect in development, i.e. expansion and use of human potential.

Attracting the wide attention of Soviet researchers, this category receives a somewhat different interpretation than Western specialists. Emphasizing the predominance of public interests over personal ones, Soviet authors see the quality of life as parameters of a "new way of life" that does not boil down to the growth of incomes of the population and the production of consumer goods, but implies a constant growth of consciousness, culture of people, including the culture of work, life, everyday behavior. , reasonable consumption. Some researchers also add here: the use of free time, political culture, a favorable social climate, a high degree of equality in social relations, social justice.

2. Practical part

The elements of any system, in turn, always have some independence of behavior. In any formulation of a scientific problem, there are always certain assumptions that put aside some insignificant parameters of individual elements. However, this micro-level of independence of the elements of the system always exists. Since the movements of elements at this level are usually of no interest to the researcher, they are usually called “fluctuations”. In our everyday life, we also focus on significant, informative events, not paying attention to small, inconspicuous and insignificant processes.

The low level of individual manifestations of individual elements allows us to speak about the existence in the system of some mechanisms of collective interaction - feedback. When the collective, systemic interaction of elements leads to the fact that certain movements of the components are suppressed, one should speak of the presence of negative feedbacks. Strictly speaking, it is precisely negative feedbacks that create systems as stable, conservative, stable combinations of elements. It is negative feedbacks that thus create the world around us as a stable system of stable systems.

Stability and resilience, however, are not immutable. Under certain external conditions, the nature of the collective interaction of elements changes radically. Positive feedback begins to play a dominant role, which do not suppress, but, on the contrary, enhance the individual movements of the components. Fluctuations, small movements, previously insignificant processes reach the macro level. This means, among other things, the emergence of a new structure, a new order, a new organization in the original system.

The moment when the original system loses its structural stability and qualitatively regenerates is determined by the system laws that operate on such system values as energy and entropy.

"It seems to me that the principle of minimum energy dissipation plays a special role in the world evolutionary process. I will formulate it as follows: if not a single state of the system (process) is permissible, but a whole set of states that are consistent with the conservation laws and connections imposed on the system (process) , then its state is realized, which corresponds to the minimum energy dissipation, or, what is the same, the minimum increase in entropy. N.N. Moiseev, Academician of the Russian Academy of Sciences.

In fairness, it should be noted that the principle of minimum energy dissipation (scattering), given above in the presentation of academician Moiseev, is not recognized as a universal natural science law. Ilya Prigozhin, in particular, pointed to the type of systems that do not obey this principle. Let us, however, leave the fundamental questions to the leading scientists. On the other hand, the use of the term “principle” rather than “law” leaves room for refinement of the wording.

The moments of a qualitative change in the original system are called state bifurcations and are described by the corresponding sections of mathematics - catastrophe theory, nonlinear differential equations, etc. The range of systems subject to such phenomena turned out to be so wide that it made it possible to speak of catastrophes and bifurcations as universal properties of matter.

Thus, the movement of matter in general can be considered as an alternation of stages of adaptive development and stages of catastrophic behavior. Adaptive development implies a change in the parameters of the system while maintaining an unchanged order of its organization. When external conditions change, parametric adaptation allows the system to adapt to new constraints imposed by the environment.

Catastrophic stages are a change in the very structure of the original system, its rebirth, the emergence of a new quality. It turns out that the new structure allows the system to move to a new thermodynamic development trajectory, which is characterized by a lower rate of entropy production, or a lower rate of energy dissipation.

The emergence of a new quality, as already noted, occurs on the basis of an increase in small random movements of elements - fluctuations. This, in particular, explains the fact that at the moment of bifurcation of the state of the system, not one, but many options for structural transformation and further development of the object are possible. Thus, nature itself limits our ability to accurately predict development, leaving, nevertheless, the possibility of important qualitative conclusions.

Thus, synergetics is entirely in line with traditional dialectics, its laws of development - the transition of quantitative changes into qualitative ones, negation, etc.

Comparative comparison of implementations of the system approach

Cybernetic	Synergistic
The self-organization of the system is associated with the stability provided by the information mechanism of self-stabilization through negative feedback, in the fight against disequilibrium	Self-organization of systems is associated: with non-equilibrium, which is the basis for the formation of order and the cause of spontaneous structural restructuring when interacting with the environment; with the self-contradiction of the "inside" of the system; with invariance and structural stability; with information optimization and positive feedback
Complex processes in the system develop due to centralized influences	Complex processes in the system develop due to local interactions of their structural elements
The purpose of the appointment and development of the system is set by the governing body	The system itself chooses the path of its development
The possibility of a complete reduction of a complex system to a cumulative analysis of its simpler components	A complex system has its own properties that determine its integrity, which are not reduced to a set of properties of its elements.
Each element of a complex system is considered in isolation	The main attention is paid to the cooperative actions of a large number of elements (wave processes)
The system is controlled by its creator or programmed	The system is self-organizing
The system is determined; structures, elements and possibilities are given, the factor of chance is introduced from the outside. The opposite option is possible - the system is absolutely random	Resonances, uncertainty, randomness, chaos can be a source of formation of new, relatively deterministic structures.
Controlled systems are in equilibrium. Disequilibrium is harmful to the homeostasis of the system	Disequilibrium is a necessary condition for self-organization; development occurs through instabilities and resonances
Time is reversible or directed in such a way that degradation of the system occurs	Time is irreversible; systems can evolve over time
For complex systems, it is believed that the greater the number of factors included in the consideration, the more accurate the result will be; striving for a complex description of simple systems	For a complex self-organizing system, at the first stages one tends to reduce the number of parameters describing it; striving for a simple description of complex systems
The analysis does not consider cardinal changes in the structures included in the system	Mainly cardinal changes of the structures included in the system are analyzed.

Glossary

Abstraction- (lat. abstraction - distraction) is: 1) mental abstraction from a number of properties of objects and relations between them; 2) an abstract concept formed as a result of refusal, rejection, disregard in the process of cognition of the non-essential aspects of the object (object, phenomenon) under consideration in order to highlight the properties that reveal its essence; 3) a synonym for "mental", "conceptual".

Abstract - based on abstraction, mental; the opposite of concrete.

Aggregation - mechanical association, the summation of any homogeneous objects, indicators, quantities in order to obtain more general, generalized, cumulative results.

Adaptation -(lat. adaptatio - to adapt) - adaptation of the structure and functions of the system (objects, organisms) to the conditions of existence.

Additive -(lat. additio - addition) - obtained by addition.

Adequacy -(lat. adaequatus - equated) - equal, identical, fully corresponding to something, to someone (for example, to the object under study, goal, task, conditions, etc.).

Axiom -(Greek axioma - significant, worthy of respect, accepted, indisputable) - a true judgment, accepted without proof as a starting point.

Alternative -(fr. alternative, lat. alter - one of two) - 1) the need to choose between mutually exclusive possibilities; 2) each of the mutually exclusive possibilities.

Analysis -(Greek analysis - dismemberment, clarification, analysis) - 1) analysis, consideration of something; dismemberment (mental or real) of an object into elements; inextricably linked with synthesis- connection of elements into a single whole; 2) a synonym for scientific research in general; 3) in formal logic - refinement of the logical form (structure) of reasoning; 4) a logical technique, a method of research, consisting in the fact that the object under study is mentally or practically divided into constituent elements (features, properties, relationships), each of which is then examined separately as part of a dismembered whole in order to identify the elements identified during the analysis connect using another logical technique - synthesis - into a whole, enriched with new knowledge.

Analogy -(gr. analogia - correspondence, similarity) - 1) the similarity of various objects according to certain properties, parameters; similarity in any respect between objects, objects, phenomena, processes, concepts; 2) similarity, similarity of objects in some of their properties, features or relationships, moreover, such objects that are generally different; 3) a logical conclusion, as a result of which knowledge about the properties, features of one object arises on the basis of its known similarity with other objects.

Byte - 1) one character of the binary alphabet, which can be represented by an eight-bit binary code; 2) 8 binary digits; 3) unit of memory capacity.

Bio -(Greek bios - life) - an integral part of compound words, indicating the attitude to life, life processes, biology.

Bit -(eng. binary - binary, digit - sign, digit) - 1) a binary unit of the amount of information, according to Shannon, obtained during the implementation of one of two equally probable events; 2) binary digit, one symbol of the binary alphabet; 3) unit of memory capacity.

Bifurcation point -(lat. bifurcus - bifurcated; bis - twice, furca - pitchfork) - a point of division, bifurcation, branching of something into two or more streams, directions.

Model validation -(lat. validation - validity) - checking the validity, validity, significance, reliability of the model by checking the compliance of the data (results) obtained during the modeling process, in particular the simulation of the object, with the experimental data obtained on the real object, for which the model was created.

Verification principle - the principle of testing the truth of a theory by comparing it with the facts of reality.

Verification (models, programs) -(lat. verus - true and facio - I do) - 1) in modeling - established authenticity, verification of the truth, adequacy of the model to the object at the level of the structure (logic) of the model; 2) in programming - proof of the correctness of programs.

real - 1) consisting of a substance; 2) the same as real (for example, in mathematics).

Virtualization -(cf. lat. virtualis - possible) - 1) a research method based on the abstraction of non-essential properties, connections, relations of objects and highlighting those that may be the most significant under certain conditions; 2) transition to a higher level of distraction in the management of specific configurations of the computer system.

Virtual- (cf. lat. virtualis - possible) - 1) one that can or should appear under certain conditions; 2) created by the imagination of the creator, user; 3) consisting in part of real hardware and software that imitates the real; 4) non-existent, but able to exist under certain conditions.

Genesis -(Greek genesis - source; origin, occurrence, birth) - 1) origin, occurrence; the birth of something, someone; the moment of origin and the subsequent process of development, which led to a certain state, type, phenomenon, thought, teaching, etc.; 2) the process of formation and formation of a developing object.

Hypothesis -(Greek hypothesis - foundation, assumption) - 1) a scientific assumption put forward to explain something and requiring experimental verification and theoretical justification in order to become a reliable theory, i.e. an assumption requiring scientific proof; 2) a possible assumption that explains the phenomenon, but the reliability of which under modern conditions cannot be proven.

Glossary -(Greek glōssa - language, little-used words; Lat. glossarium - gloss dictionary) - an explanatory dictionary of obsolete, little-used or incomprehensible words.

Epistemology -(Greek gnosis - knowledge, logos - teaching) - a theory of knowledge that studies the sources, forms and methods of scientific knowledge, the conditions for its truth, as well as the ability of a person to cognize reality.

Data- any set (combination) of signals, data or knowledge-1, considered regardless of their content, meaning, information about the object that they contain.

deductive - based on deduction; using the deductive method.

Deduction -(lat. deductio - derivation) - a logical conclusion from the general to the particular; a form of thinking, when a new thought (conclusion, conclusion) is obtained in a purely logical way from some initial thought-parcels.

Reality - objective reality in all its concreteness; a set of natural and social objects, objects, phenomena, processes; true reality as opposed to appearances.

Decomposition -(fr. decomposer - to dissolve, crush) - the division of an object (system) into structural units.

Diagnosis -(Greek diágnōsis - recognition) - determination of the state in which an object is located.

Diagnostics -(Greek diágnōstikós - capable of recognizing) - the doctrine of the methods and principles of recognizing the state in which an object is located; establishing diagnosis.

Dualism -(lat. dualis - dual) - duality, duality.

Isolate -(fr. isoler) - isolate, separate, deprive of connection with the environment.

System isomorphism -(Greek isos - equal, identical; similar; morphe - appearance, form) - correspondence (relationship) between systems, expressing the identity of their structure, structure (structural isomorphism) or functions (functional, functional isomorphism).

Hierarchy -(gr. hierarchia, hieros - sacred, archē - power) - the arrangement of parts or elements of the whole in order from the highest to the lowest in the order of their subordination.

Induction -(lat. inductio - guidance) - a method (form) of thinking, through which a general (rule, position, structure, property) is derived, inherent in all single objects of any class, a conclusion from facts to some hypothesis, general statement.

Intelligence -(lat. intellectus) - mind, reason, reason; thinking abilities.

Interpretation -(lat. interpretatio - mediation; clarification, interpretation) - here - interpretation, explanation, clarification of the meaning, meaning of something; translation into a more understandable language.

Informatics- 1) scientific discipline, covering a set of fundamental and applied areas; 2) an area of practical activity that studies the essence, patterns and solves problems of creating and using tools and technologies for collecting, processing, analyzing, interpreting and applying information, as well as solving various problems of using information, information technologies, tools, resources and structures in natural and artificial material objects, living and non-living organisms and communities.

Truth - 1) adequate reflection in the human mind of objects, phenomena, processes and patterns of objective reality such as they exist outside and independently of the cognizing subject; 2) compliance of the content of thoughts (judgments and concepts) with the object, verified by practice; 3) the objective content of human knowledge.

Iteration -(lat. iteratio - repetition) - the result of applying any repeatedly repeated operation, action, when the number of repetitions is not known in advance and stops when the desired requirement (accuracy, reliability) is reached.

infological(information-logical) model subject area - a set of information objects of the subject area and their structural relationships.

Informatics- in a broad sense - a branch of knowledge that studies the general properties and structure of scientific information, as well as the patterns and principles of its creation, transformation, accumulation, transfer and use in various fields of human activity.

Informatics- in a narrow sense - a branch of knowledge that studies the laws and methods of accumulation, transmission and processing of information using a computer.

Cybernetics- the science of management, communication and processing of information. The main object of research in cybernetics are abstract cybernetic systems: from computers to the human brain and human society.

Depending on the field of application, political, economic and social cybernetics are distinguished.

Classification -(lat. classis - category, facio - I do) - 1) distribution by class, assignment of objects (elements of a certain set) to one or another of the interrelated classes (subsets) obtained from dividing this set according to some basis, attribute or group signs; 2) the result of this process.

Composition -(lat. compositio - compilation, composition; connection) - 1) an operation that finds out the relationship of two ordered elements and the third element of a certain set, for example, producing a third from two elements; 2) construction, internal structure of some object (work).

constructive -(lat. constructio - building) - one that can be the basis of something; fruitful.

Concept -(lat. conceptio - understanding) - 1) a system of interrelated views, one or another understanding of things, phenomena, processes; 2) a single, defining concept of something; 3) the fundamental idea of any theory.

macro environment -(Greek macrós - large, long) - "external", environment - 1) human habitat; natural and social environment; 2) surrounding "participants" (objects, subjects) natural, social, material and spiritual conditions of existence and activity.

Marketing -(English marketing, from market - market, sales) - a system of measures to study the market and actively influence consumer demand in order to expand the sales of manufactured goods.

Material -(lat. materialis - material) - material, real, valid, physical.

Measure - 1) in philosophy - a category expressing dialectical unity, the relationship of qualitative and quantitative characteristics (differences and changes) of an object (subject, process, phenomenon); indicates the limit beyond which the quantity entails a change in the quality of the object and vice versa; 2) in mathematics - a generalization of the concept of the length of a segment, the area of a flat figure, the volume of a body to mathematical objects of a different, including more general nature (measures of a set, distance, similarity, adequacy, etc.);

3) in measuring technology - a) a measuring instrument designed to reproduce physical quantities of a given size; b) characteristics of accuracy (measure of accuracy), reliability (measure of reliability), etc. measurement results.

A measure of the amount of information - depending on the context, on the approach to understanding what information is, has a philosophical, measuring or mathematical content.

Microenvironment -(Greek micrós - small) - an environment adjacent directly to an object, subject, for example, interacting with it; the environment in which they are directly located and in which the “participants” considered in it directly interact.

Modeling- a research method based on replacing the original object under study with its model and working with it instead of the object, followed by transferring the results obtained on the model to the object.

Model -(target) auxiliary artificial or natural, mental (abstract or virtual) or material (real or energy) object, designed to display the most important for the subject (creator, researcher, user) from the point of view of the goal (task) set by him of the study of patterns, properties and features of the structure and functioning of the original object.

Surveillance - research method based on the target passive single perception of an object in real conditions (passive experience).

Nit (nat) - a unit of the amount of information (or entropy), in the definition of which natural logarithms are used (analogous to a bit).

Generalization - transition to a higher degree of abstraction by identifying common features of objects in the area under consideration.

An object -(lat. objectum - object) - 1) the external world existing outside of us and independently of our consciousness, which is the subject of knowledge, the practical influence of the subject; 2) the object, phenomenon, to which any activity is directed; 3) one of the basic concepts of topology, an open set that is a connected set.

Objective -(lat. objectivus - objective) - 1) existing in reality, really, outside and independently of consciousness; 2) corresponding to reality, impartial, unbiased.

Object of study, knowledge - that primary, on which the research is directed, cognition (in contrast to the subject).

Homonyms -(Greek homos - the same, onoma - name) - words that have the same sound and (or) spelling, but different meanings.

Ontology -(Greek ontos - being, logos - teaching, science) - the science of the essence, being, general patterns of being.

Operand - 1) a memory cell and registers of a computer, the contents of which must be used or changed when performing a technical operation (command); 2) intermediate product - an object or result of an information technology operation; the value on which the operation is performed.

Optimal- (lat. optimus - the best) - the best in a sense, the most favorable.

Organization -(fr. organization, late lat. organizo - I communicate a slender appearance, arrange) - here - the internal structure, interaction, arrangement, orderliness of something.

Pragmands - operands of pragmatic informational technological operations, i.e. operations that take into account the practical significance, effectiveness, value, usefulness of the operands, the useful information contained in them.

Pragmatics- (gr. pragma - business, action; pragmaticus - business, practical) - a section of semiotics that studies the relationship between sign systems and those who use them; the relationship of subjects perceiving and using any sign system to the sign system itself.

Thing - every material thing.

The subject of research, knowledge - secondary in research, cognition, what is being investigated is known in the object of research, cognition.

Primate -(lat. primatus - first place, seniority) - primacy, primacy, predominance, prevailing knowledge; headship.

Forecast -(lat., Greek prognosis - prediction, knowledge in advance) - 1) prediction, foresight of something; 2) a scientifically based judgment about the possible states of the object in the future, about alternative ways or terms for achieving these states.

Reality -(Late Latin realis - real, material) - objectively existing (phenomenon, substance) in reality, in fact, regardless of the attitude towards it.

The revolution -(lat. revolutio - turn, coup) - a deep qualitative, radical change, a sharp jump-like transition in the development of something, someone; a process of development characterized by a radical qualitative change.

Self-adjusting system- a system in which adaptation to changing conditions is ensured by automatically changing the settings while maintaining the structure and algorithm of operation or by searching for optimal (in a sense) values of the settings.

Self-learning system - a system in which, as experience is gained, an automatic change in the functioning algorithm is provided in order to ensure its optimal (in a sense) behavior.

Self-organizing system - a system in which automatically, when the operating conditions change, its structure changes in order to ensure its optimal (in a sense) behavior.

Self-adapting system - a system that maintains its performance under conditions of unforeseen changes in its properties, purpose and conditions of operation, environment, etc.

Self-referential system - self-aware, operationally closed, autonomous, dynamically (rather than statically) stable, evolving system.

Semantics- (gr. sёmantikos - denoting) - 1) semantic content<данных>, information, words, phrases; 2) a branch of semiotics that studies sign systems as a means of expressing meaning, meaning, rules for interpreting signs and expressions made up of them.

Semanda - operands of semantic informational technological operations, i.e. operations that take into account the semantic content of the operands.

Semiotics - the science of the properties of signs and sign systems.

Sinandy - operands of syntactic information technological operations, i.e. operations that take into account only the form, the structure of the operands.

Syntax -(gr. syntaxis - compilation, construction, order) - a section of semiotics that studies the structure and syntax of sign systems, composition, structure of combinations of signs and the rules for their formation, regardless of their meanings and functions.

Synthesis -(Greek synthesis - connection, composition, combination) - 1) connection (mental or real) of various elements of an object into a single whole (system); 2) mental or real connection of parts of an object dissected in the process of analysis, establishing the interaction and connections of parts and cognition of this object as a whole; 3) a method of scientific research of any object, phenomenon, consisting in the knowledge of it as a single whole, in the unity and interconnection of its parts; connection, generalization; 4) obtaining something new, the process of forming something (for example, a product, speech sounds with a special acoustic device, etc.).

System - a set of interrelated elements (objects) united to achieve a common goal, isolated from the environment, interacting with it as a whole and exhibiting systemic properties.

Dissipative system- (lat. dissipatio - dispersion) - (in physics) - a mechanical system, the total (sum of kinetic and potential) energy of which during movement, i.e. when the relative position of its constituent bodies changes, it decreases, passing into other types of energy, for example, into heat, i.e. system in which energy is dissipated.

The system is conservative- (in physics) - a mechanical system, during the movement of which its total (the sum of kinetic and potential) energy remains constant, i.e. system for which the law of conservation of mechanical energy holds.

Equilibrium system - a system in which the change of states occurs slowly through a series of equilibrium states infinitely close to each other, characterized by reversibility, equality of macroscopic parameters (temperature, pressure, etc.) and maximum entropy in conditions of isolation and the absence of external influences (fields) or rotation of the system as a whole .

Specification -(lat. specificatio: species - species, variety, facere - to do) - 1) enumeration of the specific features of something; distribution by category, classification; 2) a technical document in the form of a table with a detailed description of the product and its composition, for example, a machine, device, equipment, etc.; a document listing the conditions that a production order must satisfy (meet).

Essence and phenomenon:

essence, essence the internal content of the object, which is in the unity of all its diverse properties and relationships;
phenomenon- this or that detection of an object; external forms of its existence;
process(lat. processus - promotion) - 1) the course of a phenomenon; successive change of states, stages of development, etc.; 2) a set of sequential actions to achieve any result (technological, industrial, social, computational, etc.).

Thesaurus(Greek thesauros - stock, treasure, treasury) - 1) the totality of information that a user or an information system has; 2) a dictionary in which the semantic relationships of words are indicated; language dictionary with complete semantic information; 3) a complete systematic set<данных>and knowledge-2 from any area, allowing a person and an information system to navigate in it.

Term(lat. terminus - limit, border) - a word or phrase that accurately denotes a certain concept used in science, technology, art.

Traduction -(lat. traductio - movement) - a conclusion in which premises and conclusions (conclusions) are judgments of the same generality, i.e. when the conclusion goes from knowledge of a certain degree of generality to new knowledge, but of the same generality.

finite -(lat. finitus - final, definite, finished) - final, associated with a certain number, limited to a certain range.

Formalization - representation of any meaningful area of knowledge, problem, task in the form of a symbolic system or calculus, clearly defined conditions; representation of concepts and methods of the subject area in the terminology of formal systems.

Fundamental -(lat. fundamentum - base) - main, main.

Functional- mapping (rule of transformation, correspondence) of a set of functions into a set of numbers (for example, a definite integral of a set of functions, the parameter or parameters of which take on a certain set of values).

Function- (lat. functio - performance) - 1) duty, range of activities, purpose, role; 2) in mathematics: a) dependent variable, i.e. a quantity that changes as another quantity, called the argument, changes (linear, non-linear; logarithmic, ...); b) mapping (rule of transformation, correspondence) of one set of numbers to another set of numbers; 3) specific activity of the organism; 4) the meaning of any linguistic form.

Evolution -(lat. evolutio - deployment) - the process of change, development, a form of movement, characterized by continuous, gradual quantitative change.

Heuristic -(gr. heuriskō - I find) - 1) a system of education through leading questions; 2) a set of special logical techniques and methodological rules for theoretical research, finding the truth, discovering something new; 3) a science that studies productive creative thinking.

Experiment- an active experiment with an object under study that is scientifically delivered under natural or artificial conditions that are taken into account and / or regulated, allowing multiple repetitions.

Emergence (emergence) -(English emergent - suddenly appearing) - a system property, according to which the result of the system's behavior gives an effect that is different from the "addition" (independent connection) in any way of the results of the behavior of all the "elements" included in the system. In other words, according to this feature of the system, its properties are not reduced to the totality of properties of the parts of which it consists, and are not derived from them.

Efficient -(lat. effectivus - effective) - effective, giving the desired result; impressing.

Energy- (Greek energia - action, activity) - 1) a general quantitative measure of various forms of motion and interaction of matter; 2) active strength, perseverance, determination in achieving the goal.

Entropy -(Greek en - in, inside, trope - turn, transformation; entropia - transformation inward) - 1) in physics - one of the physical quantities characterizing the thermal state of a body or system of bodies, a measure of the internal disorder of the system (J / K); 2) in information theory - a measure of the uncertainty of a discrete random variable or a situation with a finite or countable number of outcomes.

Conclusions

Synergetics can be used as a basis for an interdisciplinary synthesis of knowledge, as a basis for a dialogue between naturalists and humanists, for cross-disciplinary communication, a dialogue and synthesis of science and art, a dialogue between science and religion, West and East (Western and Eastern world outlook).
Synergetics can provide a new methodology for understanding the evolutionary paths of systems, the causes of evolutionary crises, the threat of catastrophes, the reliability of forecasts, and the fundamental limits of predictability in ecology, economics, sociology, and geopolitics. Synergetics gives us knowledge about the constructive principles of co-evolution of complex systems at different stages of development. Therefore, synergetics can become the basis for making informed decisions and predictions in the face of uncertainty, stochastic shocks, and periodic reorganization of geopolitical structures.

Synergetics reveals the principles of non-linear synthesis: 1) the presence of various, but not just any, ways of combining structures into one complex structure, 2) the importance of the correct topology, the "configuration" of combining simple into complex, 3) combining structures as different tempo-worlds, 4) the possibility - with the correct topology of association - significant savings in material and spiritual costs and acceleration of the evolution of the whole.

Being interdisciplinary in nature, synergetics makes it possible to develop some new approaches to training and education, to effective information support for various strata of society. We are talking about education through educational computer programs and diskettes, carrying a new vision of the world and new ways of thinking, knowledge as know how, realizing the synthesis of the results of the natural and human sciences. Natural-science education is being humanized, and humanitarian education becomes impossible without new natural-science, non-linear mathematical research methods. New information technologies are becoming necessary in education.
The methodology of non-linear synthesis, founded on the scientific principles of evolution and co-evolution of the complex structures of the world, can form the basis for designing various ways of mankind into the future. Thanks to synergetics, humanity acquires a philosophy of hope.

Bibliography

Bazhenov LB Cybernetics, its subject, methods and place in the system of sciences // Philosophy of natural sciences. - M., 1966.
Povarov G.N. Norbert Wiener and his Cybernetics. M., 1990.
Wiener N. Cybernetics, or control and communication in the animal and the machine. - 2nd ed. - M., 1968.
Viner N. Cybernetics and society. - M., 1958.
Bertalanfi L. background. General systems theory - a survey of problems and results. // System Research. - M., 1969.

The cybernetic approach is that any goal-directed behavior is considered as control. Management - in a broad, cybernetic sense - is a generalization of techniques and methods accumulated by various sciences about the management of artificial objects and living organisms.

Management is understood as the process of organizing such a targeted impact on a certain part of the environment, called the control object, as a result of which the needs of the subject interacting with this object are satisfied.

The analysis of control makes it necessary to single out the trinity - the environment, the object and the subject, within which the control process is played out.

The analysis of control makes it necessary to single out the trinity - the environment, the object and the subject, within which the control process is played out (Fig.). In this case the subject feels the influence of the environment X and the object Y. If he cannot change the state of the X environment, then he can control the state of the object Y with the help of a specially organized action U. This is control.

The state of the object Y affects the state of the needs of the subject.

Subject Needs
where - the state of the i-th need of the subject, which is expressed by a non-negative number characterizing the urgency, the relevance of this need.

The subject builds his behavior in such a way as to minimize the urgency of his needs, i.e., he solves the problem of multicriteria optimization:

(3.1)

where R - resources of the subject. This dependence expresses an unknown, but existing connection of needs with the state of the environment X and the behavior U of the subject.

Let be -solution of problem (3.1), i.e., the optimal behavior of the subject, minimizing his needs A. A method for solving problem (3.1), which makes it possible to determine , is called the control algorithm

(3.2)

where  is an algorithm that allows you to synthesize control according to the state of the environment X and needs А t ,. The subject's needs change not only under the influence of the environment or object, but also independently, reflecting the subject's vital activity, which is marked by the index t.

The control algorithm , which the subject has, determines the effectiveness of its functioning in this environment. The algorithm is recurrent:

i.e., it allows us to improve the control at every step. For example, in the sense

i.e., reducing the level of their needs.

The management process as the organization of a purposeful impact on an object can be implemented both on an intuitive and on a conscious level. The first is used by animals, the second by humans. The conscious satisfaction of needs makes us decompose the control algorithm and introduce an intermediate stage - the formulation of the control goal, i.e., act according to a two-stage scheme:

At the first stage, the goal of management is determined
, and the problem is solved on an intuitive level:

where  1 is the algorithm for synthesizing the goal Z* according to the needs A t and the state of the environment X. At the second stage, the control is determined , the implementation of which ensures the achievement of the goal Z*, formed at the first stage, which leads to the satisfaction of the needs of the subject. It is at this stage that all the power of the formal apparatus can be used, with the help of which control is synthesized according to the goal Z *

where  2 - control algorithm. This algorithm is the subject of study of cybernetics as a science.

Thus, the division of the management process into two stages reflects the well-known aspects of science - informal, intuitive, expert and formal, algorithmic. If the first is still completely owned by a person, then the second is the object of application of formal approaches. Naturally, these different functions are performed by different structural elements.

The first function is performed by the subject, and the second by the control device (CU).

The management process is an information process that consists in collecting information about the progress of the process, transferring it to accumulation and processing points, analyzing incoming, accumulated and reference information, making a decision based on the analysis performed, developing an appropriate control action and bringing it to the control object. Each phase of the control process proceeds in interaction with the environment under the influence of various kinds of interference. Goals, principles and boundaries of management depend on the nature of the problem being solved.

Control system

A control system is a set of interacting objects of control and a control body, the activity of which is directed to a given control goal.

The control system solves four main control tasks: stabilization, program execution, tracking, and optimization.

The problems of system stabilization are the problems of maintaining its output values close to some constant given values, despite the effect of interference.

The task of program execution arises in cases where the specified values of controlled variables change in time in a known way.

In optimal control systems, it is required to perform the task assigned to the system in the best possible way under given real conditions and constraints. The concept of optimality must be specified for each individual case.

Before making a decision on the creation of an CS, it is necessary to consider all its stages, regardless of the technical means by which they will be implemented. Such an algorithmic analysis of control is the basis for making a decision on the creation of a control system and the degree of its automation. In this analysis, it is necessary to take into account the complexity factor of the control object:

lack of a mathematical description of the system;

stochastic behavior;

negativity to management;

non-stationarity, drift of characteristics;

irreproducibility of experiments (the developing system all the time, as it were, ceases to be itself, which imposes special requirements on the synthesis and correction of the model of the control object).

Features of a complex system often lead to the fact that the goal of controlling such an object is never fully achieved, no matter how perfect the control is.

Control systems are divided into two large classes: automatic control systems (ACS) and automated control systems (ACS). In ACS, the control of an object or system is carried out without the direct participation of a person by automatic devices. These are closed systems.

In the process of designing a control system, 2 types of thinking are involved: analysis and synthesis.

Tasks of the analysis: determination of the stability and quality of the control process in the study of automatic control systems for given disturbances.

Synthesis tasks: determination of the parameters and structure of the controller under which the control process is provided that meets the specified technical requirements (given quality of control).

Analysis: Given a system with a given structure of parameters. It is required to determine its properties and characteristics.

Synthesis: The requirements that the system must satisfy are given. Determine the structure of the system and its parameters.

The purpose of ACS design is to determine the configuration of the system, the requirements that it must satisfy, and the setting of the main parameters that satisfy the requirements for the system.

Requirements for the quality of a closed ACS:

Good disturbance compensation

Desired type of response (transient processes) to the setting input action

Adequate output signals of the actuator

Low sensitivity to changes in the parameters of control objects

Restrictions on the magnitude of the steady-state error.

In contrast to the ACS, in the ACS, the control loop includes a person who is entrusted with the functions of making the most important decisions and responsibility for the decisions made. ACS is usually understood as human-machine systems that use modern economic and mathematical methods, electronic computers (ECE) and communications, as well as new organizational principles for finding and implementing in practice the most effective control of an object (system).

The problem of elucidating from a general standpoint the regularities of the processes of self-organization and the formation of structures is posed not only by synergetics. An important role in understanding many of the essential features of these processes was played by cybernetic approach, sometimes presented as abstracting "from specific material forms" and therefore opposed to a synergetic approach that takes into account the physical foundations of the spontaneous formation of structures.

In this regard, there are sufficient grounds to note that the creators of cybernetics and modern automata theory can rightly be considered the forerunners of synergetics.

Cybernetics(from Greek. cyber netike- the art of management) is the science of managing complex systems with feedback.

The term "cybernetics" itself appeared 25 centuries ago, when the ancient Greek philosopher Plato called it the art of controlling a ship. At the beginning of the XIX century. French physicist and mathematician A.M. Ampere, creating a classification of sciences, called cybernetics the science of government. After the death of A.M. Ampere this word has been forgotten.

In 1948, the American mathematician Norbert Wiener in his book "Cybernetics ..." defined this concept as the science of control and communication in animals and machines. The originality of this science lies in the fact that it studies not the material composition of systems and not their structure (construction), but the result of the work of this class of systems.

Prior to that, N. Wiener worked for three years at the Institute of Cardiology in Mexico City. It was then that he decided to create a unified science that studies the processes of storing and processing information, management and control.

One of the most important tasks of cybernetics is the study of the control systems of living nature. The key issue in its solution was the concept feedback, the influence of consequences on the causes that cause them and determine the course of the process.

There are usually two types of feedback:

positive feedback between the system and the environment, when the external influence of the environment leads to the accumulation of internal changes in the system and the formation of new structures;
negative feedback between the system and the environment, when the external influence of the environment is reduced or nullified, and the system returns to its invariant, i.e. the deviation from the stable state is corrected after receiving information about it.

Cybernetics deals with the study of complex systems with negative feedback those. such systems that maintain an invariant state as a result of interaction with the environment.

Cybernetics arose at the intersection of mathematics, technology and neurophysiology and is an interdisciplinary approach within the framework of a new systemic paradigm, which is also used in other sciences - physics, geology, biology, sociology.

In cybernetics, the concept of a "black box" was first formulated as a device whose internal structure is unknown, but the result of exposure to it can be tracked.

In cybernetics, systems are studied by their reactions to external influences.

Cybernetics also gave a fundamental status in natural science to the concept information as a measure of system organization as opposed to the concept of entropy as a measure of disorganization.

To make the meaning of information clearer, let us consider the activity of an ideal being called "Maxwell's demon". The idea of such a being, violating the second law of thermodynamics, was outlined by the English physicist Maxwell in his book The Theory of Heat (1871). The work of the “Maxwell demon” can be represented as follows.

When a particle with a speed above average approaches the door from the compartment BUT or a particle with a speed below average approaches the door from the compartment AT, the gatekeeper opens the door and the particle passes through the hole. When a particle with a speed below the average comes from the compartment BUT or a particle with a speed above average comes from the compartment AT, the door closes.

Thus, particles of higher speed are concentrated in the compartment AT, and in the department BUT their concentration decreases. This causes an obvious decrease in entropy; and if we connect both compartments with a heat engine, we seem to get a perpetual motion machine of the second kind.

Can "Maxwell's demon" act? Yes, if it receives information from the approaching particles about their speed and the point of impact on the wall. This makes it possible to associate information with entropy.

It is possible that analogues of such “demons” operate in living systems (for example, enzymes can claim this).

The concept of information is so important that it became the title of a new scientific direction that arose on the basis of cybernetics - informatics(from the combination of the words "information" and "mathematics").

Cybernetics reveals dependencies between information and other characteristics of a system. The work of the “Maxwell demon” makes it possible to establish an inversely proportional relationship between information and entropy: with an increase in entropy, information decreases (since everything is averaged); conversely, lowering entropy increases information. The connection of information with entropy also testifies to the connection of information with energy.

Within the framework of cybernetics, other concepts are also formulated: "management", "organization", etc., which are also used by many scientific disciplines.

Cybernetics also creates new research methods, in particular, on the patterns discovered by cybernetics, based simulation method, widely used in both natural and human sciences.

The creator of cybernetics, N. Wiener, generally argues that the physical functioning of a living organism and the most modern communication machines are approximately the same in an effort to control the level of entropy using feedback.

Both systems have sensors, or receptors, that allow them to receive information from the environment at a low energy level and use it for further actions in relation to

outside world. In both cases, there are distortions of information due to the influence of the perception apparatus itself, living or artificial. The purpose of obtaining information is to increase the effectiveness of actions in the external environment. In both cases, the result of actions (and not intentions) returns to some regulatory center.

Thus, the management processes, according to N. Wiener, obey the same laws, regardless of whether they occur in society, animate or inanimate nature.

At the end of the XX century. the development of information technology has led to the creation of the global information network Internet. From a technical point of view, the Internet is an association of transnational computer networks that connect all kinds of computers that physically transmit information over all available types of lines. The Internet is decentralized, so turning off even a significant part of the computers will not affect its operation.

According to forecasts, already in the first quarter of the XXI century. The Internet will become accessible in the same way as the telephone or television, and information has already become the most important factor in the development of modern culture.

Along with the substrate (real) and structural approaches, cybernetics introduced into scientific use functional approach like another variant of the systems approach in the broad sense of the word.

The generalizing nature of cybernetic ideas and methods brings the science of control, which is cybernetics, closer to philosophy. The task of substantiating the initial concepts of cybernetics, especially such as information, control, feedback, etc., requires access to a wider, philosophical field of knowledge, where the attributes of matter are considered - the general properties of motion, patterns of cognition.

Turchin V. F.

For a cyberneticist, metaphysics cannot be just an outside hobby. We need to create universal models of the world that would allow us, for example, to interpret human thought expressed in natural language. What can be the starting point for such a bold undertaking? What concepts should be the basis? Metaphysics must answer these questions.

Turchin V. F.

Philosophy is called upon to answer such fundamental questions for every rational creature as: "Who am I?", "Where did I come from and where do I go?", "How true is my knowledge?", "What, ultimately, is the nature of things?", " What is good and what is evil?" Each time gives its own answers to these questions. These responses are significantly influenced by the current state of knowledge and production. Our philosophy is a consequence of the emergence of evolutionary theory at the end of the 19th century and cybernetics in the middle of the 20th. This can easily be seen both in the method with which we approach philosophical problems and in the answers we offer.

Norbert Wiener

"Cybernetics" is a famous book by the outstanding American mathematician Norbert Wiener (1894-1964), which played an important role in the development of modern science and gave its name to one of its most important areas. This Russian edition is a complete translation of the second American edition, published in 1961 and containing important additions to the first edition of 1948. The reader will also find in the appendices translations of some of Wiener's articles and interviews, including the last one he gave shortly before his death for the United States magazine. News and World Report. The book, written in a peculiar free style, touches upon a wide range of problems of modern science, from the sphere of technical sciences to the sphere of social sciences and the humanities. In the center - the problems of behavior and reproduction (natural and artificial) of complex control and information systems in technology, wildlife and society. The author is deeply concerned about the fate of science and scientists in the modern world and strongly condemns the use of scientific power for exploitation and war.

Sam Harris

Should we be afraid of superintelligent artificial intelligence? Neuroscientist and philosopher Sam Harris thinks it's worth it. In his opinion, we are on the verge of creating superintelligent machines, while not solving many of the problems that may arise when creating an AI that can potentially treat people in the same way as they treat ants.

Alexey Potapov

Artificial intelligence has always been considered within the "biological metaphor" - as an analogue of human intelligence. However, the artificial intelligence systems that are currently being created, which are superior to humans in solving a variety of tasks, do not at all look like humans. This applies even to such biologically inspired approaches as artificial neural networks. I will talk about how AI scientists now define the concept of intelligence, what problems stand in the way of building thinking machines, and whether the “biological metaphor” is necessary or harmful to overcome them.

Evgeny Putin

Evgeny Putin, postgraduate student of the Department of Computer Technologies, ITMO University. As part of his dissertation, Evgeny explores the problems of integrating the concept of feature selection into the mathematical apparatus of artificial neural networks. Eugene will talk about how neural networks work, what they can do now, what they will be capable of in the near future, and whether to wait for the arrival of Skynet.

Karl R. Popper

Epistemology is an English term denoting a theory of knowledge, primarily scientific knowledge. It is a theory that attempts to explain the status of science and its growth. Donald Campbell called my epistemology evolutionary because I see it as a product of biological evolution, namely Darwinian evolution by natural selection. I consider the main problems of evolutionary epistemology to be the following: the evolution of human language and the role it has played and continues to play in the growth of human knowledge; concepts (ideas) of truth and falsity; descriptions of states of affairs (states of affaires) and the way in which language selects states of affairs from the complexes of facts that make up the world, that is, reality.

Sergey Markov

At the lecture, we will discuss the second spring of artificial intelligence in facts and figures, key works in the field of artificial intelligence and machine learning in 2017. Let's talk about image recognition, speech recognition, natural language processing and other areas of research; Let's discuss new models and equipment in 2017. We will also talk about the application of AI and machine learning in business, medicine and science, as well as discuss what we expect from artificial intelligence and machine learning in 2018.

Vyacheslav Dubynin, Alexey Semikhatov

How is the brain different from a computer, and to what extent can they be compared? If the brain is much slower than modern computing technology, then why is it still not possible to create a computer as smart as the brain? Everything is sorted out in order Vyacheslav Dubynin - Doctor of Biological Sciences, Professor of the Department of Human and Animal Physiology of the Faculty of Biology of Moscow State University, presenter Alexei Semikhatov - Doctor of Physical and Mathematical Sciences, Leading Researcher of the Lebedev Physical Institute.

Recently, more and more attention of scientists is attracted by a new direction of research - emotional computing (Affective computing). The role of emotions in the evolution of natural intelligence is great, artificial intelligence still misses a lot in this regard, it is impossible to embody many of the phenomena associated with the emotional picture, with the emotional state of a person. AI scientists are actively assisted by cognitive neuroscientists, psychologists and philosophers.

Parameter name	Meaning
Article subject:	Cybernetic approach
Rubric (thematic category)	Sociology

It should be noted that within the framework of the general theory of systems, a new area of modern science has emerged - cybernetics, as one of its branches. The cybernetic approach solves system problems using mathematical and other formal methods.

This led to the emergence of new system concepts, such as ʼʼinputs and outputsʼʼ, ʼʼhierarchyʼʼ, ʼʼmodelʼʼ, ʼʼself-regulationʼʼ, ʼʼvectorʼʼ, ʼʼmatrixʼʼ, etc., which can be used to describe an almost limitless set of processes.

Cybernetics arose as a science of processes and control relationships that are built on the basis of a specific program and represent a way to implement it. This means that above a functioning system there is always something that contains in one form or another the general scheme of the corresponding process. This ʼʼsomethingʼʼ is in the proper sense a control system, where the heterogeneity (different quality) of the object's links provides a variety of forms of control.

The initial ideas of cybernetics were outlined in the historical article by A. Rosenblatt, N. Wiener, J. Bigeolo ʼʼBehavior, purposefulness and teleologyʼʼ (1943 ᴦ.). It was the first to show the fundamental unity of the problems of communication and control in nature and technology. The main idea of N. Winœra, expressed in his book, published in 1948 ᴦ., ʼʼCybernetics or control and communication in animals and machinesʼʼ, is that you can talk about living organisms in the same language as about the whole directional cars. A formal general scheme arises, which allows not only to talk about behavior in terms of systems as a whole, but also makes it possible to dynamically explain this behavior. Such a scheme leads to the general concept of a controlled (purposeful) system, which does not depend on whether such a system exists in a “live” form or not. Τᴀᴋᴎᴍ ᴏϬᴩᴀᴈᴏᴍ, cybernetics covers systems of different quality without being interested in the properties of the material from which they are made, unless it affects the organization. Further, Winer showed that both animals and machines can be included in a new and larger class of things. He considered their distinguishing feature to be the presence of homeostatic and management systems, the science of which he called ʼʼcyberneticsʼʼ (the art of the helmsman). The functioning parts of a properly functioning machine or organism maintain balance, homeostasis of the entire system. So, it turned out to be possible to speak about animals (including humans) and about machines in the same language, which is suitable for describing any ʼʼreasonableʼʼ systems.

Cybernetics in the study of real systems seeks not just to describe them with the help of formal systems, but to use such a description to help understand (explain) how real systems work. This is usually done by building efficient and dynamic models, breaking down the way they function into algorithmic procedures.
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A feature of modeling is that, unlike hypotheses, models in it do not compete, but complement each other. In this way, they make it possible to study multidimensional phenomena with the help of a set of low-dimensional representations. With the help of computers, models are built as probabilistic pictures of the world, replacing deterministic ones. This means that, in addition to the real, the researcher also has access to the possible, which is not closely related to the observed facts. This point is heuristic in nature: the researcher has the opportunity to consider much more situations than they actually exist, and predict options for future scenarios.

At the same time, negative feedback, as it were, makes the behavior of the system tend to the prescribed limit (models as prototypes) and, therefore, there is nothing absurd or supernatural in the fact that the behavior of the system is determined by

rather the future than the past state of it. With this understanding, teleology (purposefulness) quickly ceases to be a scarecrow for the biological and social sciences.

The cybernetic method as an intellectual procedure for cognizing reality can be considered as a method of analogies. As an example, we can give a flowchart 3, - the application of this method in the study of the models proposed by A. Mol. This diagram, resembling a block diagram of a computer program, reflects the various stages of cybernetic research. The latter begins with finding an analogy, on which a certain number of restrictive conditions are then imposed, characterized by the following features.

1. The creator of the model starts by finding a speculative construction, an image of some reality, and examines how justified it is. Further, the researcher formulates the conclusions arising from this representation and checks the compliance of at least some of them with the observed reality and the facts collected by experts in this field.

2. The researcher proceeds to establish how far the analogy he is considering is far from reality. He must understand why it is exactly the way it is (insufficiently complete correspondence to the real facts, false, etc.). To do this, the researcher must intellectually

Discipline your intuitive thinking to introduce an explication: interpretation, replacement of an inaccurate image, concept, symbol with a more accurate one.

3. Raising the image under consideration to the rank of analogy (analogy model), the researcher checks it: do the phenomena that he temporarily took into account have such a large “weight” that it is extremely important to make significant corrections to the image of the main phenomenon. In this way, he establishes the degree of heuristic value of the given analogy (the materiality test situation). If this situation occurs, then the discovered value is evidence of the value of the underlying image.

4. Now the researcher establishes the scales (for example, statistical values) under which this analogy is valid. At the same time, the limits of variability of these values (validity area) are also established, beyond which the phenomenon under study changes its character and needs other types of analogies that precede structural studies at other levels.

5. Next, the researcher develops an analogy in relation to the main area. At the same time, at all stages, he seeks to reduce the description to mechanisms, the real examples of which he knows and which he is able to model in all details. The researcher, as it were, ʼʼcleansʼʼ, simplifies them and does this, in particular, with the help of schemes, graphs of the type that are used by programmers to express procedures implemented on a computer.

6. The formulation and detailed description of the proposed model constitute the first result obtained with this approach. The latter serves to integrate different concepts, ʼʼsimplificationʼʼ of thought, thanks to which a large number of disparate entities is reduced to a small number of elementary entities in accordance with Occam's principle: ʼʼEntities should not be increased without extremely important stiʼʼ. The applied models (mathematical, graphic) provide a significant compression (coding) of information and the possibility of "using it to describe a wide class of phenomena. Such a description is, finally, a means of qualitatively characterizing the phenomenon under study and a means of influencing it, that is, a tool for mastering reality.

7. At the same time, consideration of the model immediately raises some questions that require answers and clarifications. This contributes to further experimental work, a new search for facts.

So, the desire to create generalizing theories and teachings led to the emergence of a systematic approach associated with the transition to a structural-functional study of various social systems from the point of view of the functions they perform in relation to a broader whole. This predetermined two of its basic principles.

1. Allocation of the structure of an object as a kind of invariant characterizing the principles of the structure of this object.

2. Functional description of this structure.

At the same time, the merit of T. Parsons is essentially that he connected these principles for the study of social systems, developed the cybernetic idea of the general in the universe.

Cybernetic approach - concept and types. Classification and features of the category "Cybernetic approach" 2017, 2018.