The significant problems we face cannot be solved at the same level of thinking that we created them with.
Albert Einstein
Fundamentals of systems theory
The emergence of systems theory was due to the need to generalize and systematize knowledge about systems that were formed in the process of formation and historical development some "systemic" ideas. The essence of the ideas of these theories was that each object of the real world was considered as systems, i.e. was a collection of parts that made up a single whole. The preservation of the integrity of any object was ensured by the connections and relationships between its parts.
The development of a systemic worldview took place over a long historical period, within which the following important postulates were substantiated:
- 1) the concept of "system" reflects internal order a world that has its own organization and structure, as opposed to chaos (lack of organized order);
- 2) the whole is greater than the sum of its parts;
- 3) to know the part is possible only with the simultaneous consideration of the whole;
- 4) parts of the whole are in constant interconnection and mutual dependence.
The process of integration of systemic views, a large amount of empirical knowledge about systems in various scientific fields, and above all in philosophy, biology, physics, chemistry, economics, sociology, cybernetics, led to the XX century. to the need for theoretical generalization and substantiation of "systemic" ideas in independent theory systems.
One of the first who made an attempt to substantiate the system theory of systems organization was a Russian scientist A. A. Bogdanov, who in the period from 1912 to 1928 developed " general organizational science. At the heart of Bogdanov's work "Tectology. General Organizational Science" lies next idea: the existence of patterns of organization of parts into a single whole (system) through structural relationships, the nature of which can contribute to organization (or disorganization) within the system. In ch. 4 we will dwell in more detail on the main provisions of the general organizational science, which A. A. Bogdanov also called tectology. These provisions are currently becoming more relevant due to the need for dynamic development of socio-economic systems.
System theory was further developed in the works of the Austrian biologist L. von Bertalanffy. In the 1930s he substantiated a series system provisions, which combined the knowledge available at that time in the field of systems research different nature. These provisions formed the basis of the generalized concept general systems theory(OTS), the conclusions from which made it possible to develop a mathematical apparatus for describing systems of various types. The scientist saw his task in exploring the commonality of concepts, the laws of existence and methods for studying systems based on the principle of isomorphism (similarities) as universal scientific categories and the fundamental basis for the development of scientific knowledge about systems at the interdisciplinary level. Within the framework of this theory, an attempt was made to quantify and explore such fundamental concepts as "expediency" and "integrity".
An important result of the work of L. von Bertalanffy was the substantiation of the concept complex open system, within which its vital activity is possible only when interacting with the environment on the basis of the exchange of resources (material, energy and information) necessary for its existence. It should be noted that the term "total systems theory” in the scientific community has been seriously criticized due to the high level of its abstraction. The term "general" was rather deductive in nature, as it allowed to generalize theoretical conclusions about the patterns of organization and functioning of systems of different nature, it was a scientific and methodological concept for studying objects as systems and methods for describing them in the language of formal logic.
The GTS was further developed in the works of the American mathematician M. Mesarovich who suggested mathematical apparatus for describing systems! , which allows you to model system objects, the complexity of which is determined by the number constituent elements and the type of their formalized description. He justified the possibility of mathematical representation systems as functions, whose arguments are the properties of its elements and characteristics of the structure.
Mathematical substantiation of the patterns of connection of elements in the system and the description of their connections was presented to them with the help of mathematical means, i.e. using differential, integral, algebraic equations or in the form of graphs, matrices and graphs. Great importance in his mathematical theory of systems, M. Mesarovich attached importance to the study of control systems, since it is the control structure that reflects the nature of functional connections and relationships between elements, which largely determine its state and behavior as a whole. Based on the use of mathematical tools, a structure was developed
tour-functional method (approach) of describing the control system as unified system information processing (emergence, storage, transformation and transmission). The control system was considered as staged system decision-making based on formalized procedures. The use of the structural-functional approach to the study of systems allowed M. Mesarovich to create a theory hierarchical multilevel systems*, which has become an applied direction in the further development of the theory of systems management.
In 1960-1970. system ideas began to penetrate into different areas of scientific knowledge, which led to the creation subject systems theories, those. theories that investigated the subject aspects of the object based on systemic principles: biological, social, economic systems, etc. Gradually, the generalization and systematization of knowledge about systems of different nature led to the formation of a new scientific and methodological direction in the study of phenomena and processes, which is currently called systems theory.
Thus, in 1976, the Institute for System Research of the USSR Academy of Sciences was established in Moscow. The purpose of its creation was to develop the methodology of system research and system analysis. A great contribution to this matter was made by many Soviet scientists: V. G. Afanasiev, I. V. Blauberg, D. M. Gvishiani, D. S. Kontorov, I. I. Moiseev, V. I. Sadovsky, A. I. Uemov, E. G. Yudin and many others.
Soviet philosopher AT. I. Sadovsky noted: “The process of integration leads to the conclusion that many problems will receive correct scientific coverage only if they are based simultaneously on social, natural and Technical science. This requires the application of the results of research by various specialists - philosophers, sociologists, psychologists, economists, engineers. In connection with the strengthening of the processes of integration of scientific knowledge, a need arose for the development of systemic research.
Philosopher A. I. Uyomov in 1978 he published a monograph "Systems approach and general systems theory", in which he proposed his version of the parametric theory of systems. The methodological basis of this theory was the provisions of materialistic dialectics, in particular the method of ascent from the abstract to the concrete. In this theory, the author defined a number of system concepts, regularities of systems and their parametric properties. In particular, he considered the concept of "system" as a generalized philosophical category, reflecting “... universal aspects, relations and connections between real objects in a certain historical and logical sequence» .
I. V. Blauberg and E. G. Yudin believed that "the method of a holistic approach has importance in the formation of higher levels of thinking, namely the transition from the analytical stage to the synthetic one, which directs the cognitive process to a more comprehensive and deep knowledge of phenomena. The development of a holistic approach in the study of systems of different nature led to the development of universal theoretical provisions, which were combined into a single theoretical and methodological research base as an interdisciplinary science called systems theory.
The further development of systems theory went along three main scientific directions: systemonomy, systemology and systems engineering.
Systemonomy(from Greek. nomos- law) - the doctrine of systems as a manifestation of the laws of Nature. This trend is a philosophical justification for a systemic worldview that combines a systemic ideal, a systemic method, and a systemic paradigm.
Note!
The main thesis of systems theory is: "Any object of study is an object-system, and any object-system belongs to at least one system of objects of the same kind." This provision is fundamental in the formation of systemic views and objective perception of the world of Man and the world of Nature as interrelated objects (phenomena, processes) relating to systems of different nature.
In the late 1950s - early 1960s. a new methodological direction for the study of complex and large systems - system analysis. As part of a system analysis, difficult problems designing systems with specified properties, the search for alternative solutions and the choice of the optimal one for a particular case is carried out.
In 1968, a Soviet scientist V. T. Kulikov suggested the term "systemology"(from Greek. logos- word, doctrine) to refer to the science of systems. Within the framework of this science, all variants of existing theories about systems are combined, including general systems theory, specialized systems theories and systems analysis.
Systemology as an interdisciplinary science at a qualitatively new level integrates theoretical knowledge about the concepts, laws and patterns of existence, organization, functioning and management of systems of various nature in order to create a holistic system methodology for studying systems. Systemology generalizes not only scientific knowledge about systems, their origin, development and transformation, but also studies the problems of their self-development based on the theory of synergetics.
Research in the field cybernetics (II. Wiener), development of technical and computer systems who initiated the formation new system"man - technology", required the development of applied system theories, such as operations research, automata theory, algorithm theory, etc. Thus, a new direction appeared in the development of a systematic approach called "system engineering". It should be noted that the concept of "system" in combination with the concept of "technology" (from the Greek. techne- art of application, skill) was considered as a complex of general and particular methods practical application system principles and methods for describing the state and behavior of systems in mathematical language.
For the first time in Russia, this term was introduced in the 1960s. Soviet scientist, professor of the Department of Cybernetics MEPhI G. N. Povarov. Back then, it was considered an engineering discipline, studying the design, creation, testing, and operation. complex systems technical and socio-technical purposes. Abroad, this term arose between the two world wars of the 20th century. as a combination of two concepts of engineering art (from English, system design- development, design technical systems) and engineering (English, systems engineering- design, creation of systems, system development technique, system development method), which combined different areas of science and technology about systems.
System engineering - scientific and applied direction that studies the system-wide properties of system-technical complexes (STC).
System ideas more and more penetrated into private theories of systems of different nature, therefore the main provisions of the theory of systems become the fundamental basis of modern system research, systemic outlook.
If systemology mainly uses qualitative ideas about systems based on philosophical concepts, then systems engineering operates with quantitative ideas and relies on the mathematical apparatus of their modeling. In the first case, these are the theoretical and methodological foundations of systems research, in the second case, the scientific and practical foundations of design and the creation of systems with given parameters.
The constant development of systems theory has made it possible to combine the subject-content (ontological) and epistemological (epistemological) aspects of theories about systems and form system-wide provisions that are considered as three basic system-wide laws of systems(evolution, hierarchies and interactions). The law of evolution explains the target orientation of the creation of natural and social systems, their organization and self-organization. The law of hierarchy determines the type of structural relations in complex multi-level systems, which are characterized by orderliness, organization, interaction between the elements of the whole. The hierarchy of relations is the basis for building a management system. The law of interaction explains the presence of exchange processes (substance, energy and information) between the elements in the system and the system with the external environment to ensure its vital activity.
The subject of research in systems theory is complex objects - systems. The object of study in systems theory is the processes of creation, operation and development of systems.
Systems theory studies:
- various classes, types and types of systems;
- device of the system (structure and its types);
- composition of the system (elements, subsystems);
- state of the system;
- basic principles and patterns of behavior of systems;
- processes of functioning and development of systems;
- the environment within which the system is identified and organized, as well as the processes occurring in it;
- environmental factors affecting the functioning of the system.
Note!
In systems theory, all objects are considered as systems and are studied in the form of generalized (abstract) models. These models are based on the description of formal relationships between its elements and various factors external environment, influencing its state and behavior. The results of the study are explained only on the basis of interactions elements (components) of the system, i.e. on the basis of its organization and functioning, and not on the basis of the content (biological, social, economic, etc.) of the elements of systems. The specificity of the content of systems is studied by the subject theories of systems (economic, social, technical, etc.).
In systems theory, a conceptual apparatus was formed, which includes such system-wide categories as goal, system, element, connection, relationship, structure, function, organization, management, complexity, openness, etc.
These categories are universal for all scientific studies of the phenomena and processes of the real world. In systems theory, such categories as the subject and object of research are defined. The subject of the study is the observer, who plays an important role in determining the purpose of the study, the principles for separating objects as elements from the environment and arranging them to be combined into a whole object-system.
The system is considered as a kind of unified whole, consisting of interrelated elements, each of which, having certain properties, contributes to unique characteristics whole. Inclusion observer into the system of mandatory categories of systems theory made it possible to expand its main provisions and better understand the essence of system research (system approach). The main principles of systems theory include the following:
- 1) concept "system" and the concept of "environment" are the basis of systems theory and are of fundamental importance. L. von Bertalanffy defined a system as "a set of elements that are in certain relationships with each other and with the environment";
- 2) the relationship of the system with the environment is hierarchical and dynamic;
- 3) the properties of the whole (system) are determined by the nature and type of connections between elements.
Consequently, the main position of the theory of systems is that any object of study as a system must be considered in close relationship with the environment. On the one hand, the elements of the system influence each other through mutual connections in the exchange of resources; on the other hand, the state and behavior of the whole system creates changes in its environment. These provisions form the basis of systemic views (systemic worldview) and the principle of systemic research of real world objects. The presence of interrelations between all phenomena in nature and society is determined by the modern philosophical concept of cognition of the World as an integral system and process of world development.
The methodology of systems theory was formed on the basis of the fundamental laws of philosophy, physics, biology, sociology, cybernetics, synergetics and other system theories.
The main methodological principles of systems theory are:
- 1) stable-dynamic states of the system while maintaining the external form and content in the conditions of interaction with the environment - integrity principle;
- 2) division of the whole into elementary particles - discreteness principle;
- 3) formation of links during the exchange of energy, information and matter between the elements of the system and between the integral system and its environment - principle of harmony;
- 4) building relationships between the elements of the whole education (system management structure) - principle of hierarchy;
- 5) the relationship of symmetry and dissymmetry (asymmetry) in nature as the degree of correspondence between the description of a real system by formal methods - the principle of adequacy.
In systems theory, methods of system modeling are widely used, as well as the mathematical apparatus of a number of theories:
- sets (formally describes the properties of the system and its elements based on mathematical axioms);
- cells (subsystems) with certain boundary conditions, and between these cells there is a transfer of properties (for example, a chain reaction);
- networks (studies the functional structure of connections and relationships between elements in the system);
- graphs (studies relational (matrix) structures represented in a topological space);
- information (studies ways of informational description of a system-object based on quantitative characteristics);
- cybernetics (studies the control process, i.e. the transfer of information between the elements of the system and between the system and the environment, taking into account the feedback principle);
- automata (the system is considered from the point of view of the "black box", i.e. the description of the input and output parameters);
- games (explores the system-object from the point of view of "rational" behavior under the condition of obtaining the maximum gain with minimal losses);
- optimal solutions(allows you to mathematically describe the conditions for choosing the best solution from alternative possibilities);
- queues (based on methods for optimizing the maintenance of elements in the system by data streams for bulk requests).
In modern systems studies of economic and social systems, more attention is paid to means of describing complex processes of dynamic stability, which are studied in the theories of synergetics, bifurcations, singularities, catastrophes, etc., which are based on the description of nonlinear mathematical models of systems.
- Mesarovic M., Takahara J. General systems theory: mathematical foundations/ ed.S. V. Emelyanova; per. from English. E. L. Nappelbaum. M.: Mir, 1978. Bertalanfi L. background. History and status of general systems theory // System Research: Yearbook. 1972. M.: Nauka, 1973. S. 29.
Iskander Khabibrakhmanov wrote material on the theory of systems, the principles of behavior in them, relationships and examples of self-organization for the “Games Market” column.
We live in a complex world and do not always understand what is happening around. We see people who become successful without deserving it and those who are really worthy of success, but remain in obscurity. We are not sure about tomorrow, we are closing more and more.
To explain things we don't understand, we invented shamans and fortune-tellers, legends and myths, universities, schools and online courses, but it didn't seem to help. When we were in school, we were shown the picture below and asked what would happen if we pulled a string.
Over time, most of us have learned to give the correct answer to this question. However, we then went to open world, and our tasks started looking like this:
This led to frustration and apathy. We have become like the wise men in the parable of the elephant, each of whom sees only a small part of the picture and cannot draw a correct conclusion about the object. Each of us has our own misunderstanding of the world, it is difficult for us to communicate it with each other, and this makes us even more lonely.
The fact is that we live in the age of a double paradigm shift. On the one hand, we are moving away from the mechanistic paradigm of society inherited from the industrial age. We understand that inputs, outputs and capacities do not explain the diversity of the world around us, and often it is much more influenced by the socio-cultural aspects of society.
On the other hand, a huge amount of information and globalization lead to the fact that instead of an analytical analysis of independent quantities, we must study interdependent objects, indivisible into separate components.
It seems that our survival depends on the ability to work with these paradigms, and for this we need a tool, just as we once needed tools for hunting and tilling the land.
One such tool is systems theory. Below are examples from systems theory and its general provisions there will be more questions than answers and hopefully some inspiration to learn more about it.
Systems theory
Systems theory is a fairly young science at the junction a large number fundamental and applied sciences. This is a kind of biology from mathematics, which deals with the description and explanation of the behavior of certain systems and the commonality between this behavior.
There are many definitions of the concept of a system, here is one of them. System - a set of elements that are in relationships, which forms a certain integrity of structure, function and processes.
Depending on the objectives of the research, the systems are classified:
- by the presence of interaction with the outside world - open and closed;
- by the number of elements and the complexity of the interaction between them - simple and complex;
- if possible, observations of the entire system - small and large;
- by the presence of an element of randomness - deterministic and non-deterministic;
- by the presence of goals in the system - casual and purposeful;
- according to the level of organization - diffuse (random walks), organized (the presence of a structure) and adaptive (the structure adapts to external changes).
Also, systems have special states, the study of which gives an understanding of the behavior of the system.
- sustainable focus. With small deviations, the system returns to its original state again. An example is a pendulum.
- Unstable focus. A small deviation brings the system out of equilibrium. An example is a cone placed with a point on a table.
- Cycle. Some states of the system are cyclically repeated. An example is the history of different countries.
- Complex behavior. The behavior of the system has a structure, but it is so complex that it is not possible to predict the future state of the system. An example is stock prices on the stock exchange.
- Chaos. The system is completely chaotic, there is no structure in its behavior.
Often when working with systems, we want to make them better. Therefore, we need to ask ourselves the question in what special state we want to bring it. Ideally, if the new state of interest to us is a stable focus, then we can be sure that if we achieve success, then it will not disappear the next day.
Complex systems
We are increasingly seeing complex systems around us. Here I did not find sounding terms in Russian, so I have to speak in English. There are two fundamentally different concepts of complexity.
The first (complicatedness) - means some complexity of the device, which is applied to fancy mechanisms. This kind of complexity often makes the system unstable to the slightest changes in the environment. So, if one of the machines stops at the plant, it can disable the entire process.
The second (complexity) - means the complexity of behavior, for example, biological and economic systems (or their emulations). This behavior, on the contrary, persists even with some changes. environment or the state of the system itself. So, when a major player leaves the market, the players will share his share less among themselves, and the situation will stabilize.
Often complex systems have properties that can lead the uninitiated into apathy, and make working with them difficult and intuitive. These properties are:
- simple rules complex behavior,
- butterfly effect or deterministic chaos,
- emergence.
Simple rules for complex behavior
We are used to the fact that if something exhibits complex behavior, then it is most likely complex internally. Therefore, we see patterns in random events and try to explain things that are incomprehensible to us by the machinations of evil forces.
However, this is not always the case. A classic example simple internal device and tricky external behavior is the game "Life". It consists of a few simple rules:
- the universe is a checkered plane, there is an initial arrangement of living cells.
- at the next moment of time, a living cell lives if it has two or three neighbors;
- otherwise it dies of loneliness or overpopulation;
- in an empty cell, next to which there are exactly three living cells, life is born.
In general, writing a program that will implement these rules will require five to six lines of code.
At the same time, this system can produce quite complex and beautiful templates behavior, so without seeing the rules themselves it is difficult to guess. And it's certainly hard to believe that this is implemented in a few lines of code. Perhaps the real world is also built on several simple laws, which we have not yet derived, and the entire infinite variety is generated by this set of axioms.
Butterfly Effect
In 1814, Pierre-Simon Laplace proposed a thought experiment, which consisted in the existence of an intelligent being capable of perceiving the position and speed of every particle of the universe and knowing all the laws of the world. The question was the theoretical ability of such a being to predict the future of the universe.
This experiment caused a lot of controversy in scientific circles. Scientists, inspired by progress in computational mathematics, tended to answer yes to this question.
Yes, we know that the principle of quantum uncertainty excludes the existence of such a demon even in theory, and predicting the position of all particles in the world is fundamentally impossible. But is it possible in simpler deterministic systems?
Indeed, if we know the state of the system and the rules by which they change, what prevents us from calculating the next state? Our only problem might be a limited amount of memory (we can store numbers with limited precision), but all calculations in the world work this way, so this should not be a problem.
Not really.
In 1960, Edward Lorenz created a simplified weather model, consisting of several parameters (temperature, wind speed, pressure) and the laws by which the state at the next time is obtained from the current state, representing a set of differential equations.
dt = 0.001
x0 = 3.051522
y0 = 1.582542
z0 = 15.623880
xn+1 = xn + a(-xn + yn)dt
yn+1 = yn + (bxn - yn - znxn)dt
zn+1 = zn + (-czn + xnyn)dt
He calculated the values of the parameters, displayed them on the monitor and built graphs. It turned out something like this (graph for one variable):
After that, Lorentz decided to rebuild the graph, taking some intermediate point. It is logical that the graph would have turned out exactly the same, since the initial state and the transition rules have not changed in any way. However, when he did, something unexpected happened. In the graph below, the blue line represents the new set of parameters.
That is, at first both graphs go very close, there are almost no differences, but then the new trajectory moves further and further away from the old one, starting to behave differently.
As it turned out, the reason for the paradox lay in the fact that in the computer's memory all data was stored with an accuracy of up to the sixth decimal place, and was displayed with an accuracy of up to the third. That is, a microscopic change in the parameter led to a huge difference in the trajectories of the system.
It was the first deterministic system to have this property. Edward Lorenz gave it the name The Butterfly Effect.
This example shows us that sometimes events that seem unimportant to us end up having a huge impact on outcomes. The behavior of such systems is impossible to predict, but they are not chaotic in nature either. literally of this word, because they are determined.
Moreover, the trajectories of this system have a structure. AT three-dimensional space the set of all trajectories looks like this:
What is symbolic, it looks like a butterfly.
emergence
Thomas Schelling, an American economist, looked at maps of the distribution of racial classes in various American cities, and observed the following pattern:
This is a map of Chicago and here different colors the places of residence of people of different nationalities are depicted. That is, in Chicago, as in other cities in America, there is a fairly strong racial segregation.
What conclusions can we draw from this? The first thing that comes to mind is: people are intolerant, people do not accept and do not want to live with people who are different from them. But is it?
Thomas Schelling proposed the following model. Imagine a city in the form of a checkered square, people of two colors (red and blue) live in the cells.
Then almost every person from this city has 8 neighbors. It looks something like this:
Moreover, if a person has less than 25% of neighbors of the same color, then he randomly moves to another cell. And so it continues until each resident is satisfied with his position. The inhabitants of this city cannot be called intolerant at all, because they only need 25% of people like them. In our world, they would be called saints, a real example of tolerance.
However, if we start the process of moving, then from the random location of the inhabitants above, we will get the following picture:
That is, we get a racially segregated city. If, instead of 25%, each resident wants at least half of the neighbors like him, then we will get almost complete segregation.
At the same time, this model does not take into account such things as the presence of local temples, shops with national utensils, and so on, which also increase segregation.
We are accustomed to explaining the properties of a system by the properties of its elements and vice versa. However, for complex systems, this often leads us to incorrect conclusions, because, as we have seen, the behavior of the system at the micro and macro levels can be opposite. Therefore, often going down to the micro level, we try to do the best, but it turns out as always.
This property of a system, when the whole cannot be explained by the sum of its elements, is called emergence.
Self-organization and adaptive systems
Perhaps the most interesting subclass of complex systems are adaptive systems, or systems capable of self-organization.
Self-organization means that the system changes its behavior and state, depending on changes in the external world, it adapts to changes, constantly transforming itself. Such systems everywhere, almost any socio-economic or biological, just like the community of any product, are examples of adaptive systems.
Here is a video of the puppies.
At first, the system is in chaos, but when an external stimulus is added, it becomes more orderly and quite nice behavior appears.
Ant Swarm Behavior
The foraging behavior of an ant swarm is a perfect example of an adaptive system built around simple rules. When looking for food, each ant wanders randomly until it finds food. Having found food, the insect returns home, marking the path it has traveled with pheromones.
At the same time, the probability of choosing a direction when wandering is proportional to the amount of pheromone (smell strength) on this path, and over time, the pheromone evaporates.
The efficiency of the ant swarm is so high that a similar algorithm is used to find the optimal path in graphs in real time.
At the same time, the behavior of the system is described by simple rules, each of which is critical. So the randomness of the wander allows finding new food sources, and the evaporability of the pheromone and the attractiveness of the path, proportional to the strength of the smell, allows you to optimize the length of the route (on a short path, the pheromone will evaporate more slowly, since new ants will add their pheromone).
Adaptive behavior is always somewhere between chaos and order. If there is too much chaos, then the system reacts to any, even insignificant, change and cannot adapt. If there is too little chaos, then stagnation is observed in the behavior of the system.
I have observed this phenomenon in many teams where the presence of clear job descriptions and rigidly regulated processes made the team toothless, and any noise outside unsettled it. On the other hand, the lack of processes led to the fact that the team acted unconsciously, did not accumulate knowledge, and therefore all its unsynchronized efforts did not lead to a result. Therefore, the construction of such a system, and this is the task of most professionals in any dynamic field, is a kind of art.
In order for the system to be capable of adaptive behavior, it is necessary (but not sufficient):
- openness. closed system cannot adapt by definition, as she knows nothing about the outside world.
- Presence of positive and negative feedbacks. Negative feedbacks keep the system in a favorable state as they reduce the response to outside noise. However, adaptation is also impossible without positive feedbacks that help the system move to a new, better state. When it comes to organizations, processes are responsible for negative feedbacks, while new projects are responsible for positive feedbacks.
- Variety of elements and relationships between them. Empirically, increasing the variety of elements and the number of connections increases the amount of chaos in the system, so any adaptive system must have necessary quantity and both. Diversity also allows for a smoother response to change.
Finally, I would like to give an example of a model that emphasizes the need for a variety of elements.
It is very important for a bee colony to maintain a constant temperature in the hive. Moreover, if the temperature of the hive falls below the desired for a given bee, she begins to flap her wings to warm the hive. Bees have no coordination and the desired temperature is built into the bee's DNA.
If all the bees have the same desired temperature, then when it drops below, all the bees will begin to flap their wings at the same time, quickly warm the hive, and then it will also quickly cool down. The temperature graph will look like this:
And here is another graph where the desired temperature for each bee is randomly generated.
The temperature of the hive is kept at a constant level, because the bees are connected to the heating of the hive in turn, starting from the most "freezing".
That's all, finally, I want to repeat some of the ideas that were discussed above:
- Sometimes things are not quite what they seem.
- Negative feedback helps you stay put, positive feedback helps you move forward.
- Sometimes, to make it better you need to add chaos.
- Sometimes simple rules are enough for complex behavior.
- Appreciate variety, even if you're not a bee.
Cybernetics Wiener
Bogdanov's tectology
A.A. Bogdanov "General organizational science (tectology)", v.1 - 1911, v.3 - 925
Tektology should study the general patterns of organization for all levels. All phenomena are continuous processes of organization and disorganization.
Bogdanov owns the most valuable discovery that the level of organization is the higher, the stronger the properties of the whole differ from the simple sum of the properties of its parts.
A feature of Bogdanov's tectology is that the main attention is paid to the patterns of organization development, consideration of the relationship between stable and changeable, the importance of feedback, taking into account the organization's own goals, and the role of open systems. He emphasized the role of modeling and mathematics as potential methods for solving problems of tectology.
N. Wiener "Cybernetics", 1948
The science of control and communication in animals and machines.
"Cybernetics and society'. N. Wiener analyzes the processes taking place in society from the standpoint of cybernetics.
First International Congress on Cybernetics - Paris, 1966
Wiener cybernetics is associated with such advances as the typification of system models, the identification of the special significance of feedback in the system, the emphasis on the principle of optimality in the control and synthesis of systems, the awareness of information as a general property of matter and the possibility of its quantitative description, the development of modeling methodology in general and, in particular, the idea mathematical experiment with the help of a computer.
Cybernetics is the science of optimal control of complex dynamic systems (A.I. Berg)
Cybernetics is the science of systems that perceive, store, process and use information (A.N. Kolmogorov)
In parallel, and, as it were, independently of cybernetics, another approach to systems science was being developed - general systems theory.
The idea of constructing a theory applicable to systems of any nature was put forward by the Austrian biologist L. Bertalanffy.
L. Bertalanffy introduced the concept open system and theory applicable to systems of any nature. The term "general systems theory" was used orally in the 30s, after the war - in publications.
Bertalanffy saw one of the ways to implement his idea in looking for the structural similarity of the laws established in various disciplines, and, generalizing them, to derive system-wide patterns.
One of the most important achievements of Bertalanffy is his introduction of the concept of an open system.
In contrast to the Wiener approach, where intrasystem feedbacks are studied, and the functioning of systems is considered simply as a response to external influences, Bertalanffy emphasizes special meaning exchange of matter, energy and information with an open environment.
The starting point of the general systems theory as an independent science can be considered 1954, when the society for promoting the development of the general systems theory was organized.
Your first yearbook General systems The Society published in 1956
In an article in the first volume of the yearbook, Bertalanffy pointed out the reasons for the emergence of a new branch of knowledge:
· There is a general tendency to achieve unity of various natural and social sciences. Such unity can be the subject of study of the UTS.
· This theory can be an important means of forming rigorous theories in the sciences of wildlife and society.
By developing the unifying principles that take place in all fields of knowledge, this theory will bring us closer to the goal of achieving the unity of science.
All this can lead to the achievement of the necessary unity of scientific education.
Ampère is a physicist, Trentovsky is a philosopher, Fedorov is a geologist, Bogdanov is a physician, Wiener is a mathematician, Bertalanffy is a biologist.
This once again indicates the position of the general systems theory - at the center of human knowledge. According to the degree of generality, J. van Gig puts the general theory of systems on the same level as mathematics and philosophy.
Close to GTS on the tree of scientific knowledge are other sciences dealing with the study of systems: cybernetics, teleology, information theory, engineering communication theory, computer theory, systems engineering, operations research and related scientific and engineering areas.
2. Definition of the concept of "system", the subject of systems theory.
System- a set of elements that are in relationships and connections with each other, which forms a certain integrity, unity.
All definitions can be divided into three groups.
Three groups of definitions:
- a complex of processes and phenomena, as well as connections between them, existing objectively, regardless of the observer;
- a tool, a method of studying processes and phenomena;
- a compromise between the first two, an artificially created complex of elements for solving a complex problem.
First group
The task of the observer is to isolate the system from the environment, find out the mechanism of functioning and, based on this, influence it in the right direction. Here the system is the object of research and control.
Second group
The observer, having some purpose, synthesizes the system as an abstract representation of real objects. System - a set of interrelated variables representing the characteristics of the objects of this system (coincides with the concept of a model).
Third group
The observer not only singles out the system from the environment, but also synthesizes it. The system is a real object and at the same time an abstract reflection of the connections of reality (system engineering).
GENERAL SYSTEM THEORY – with special-scientific and logical-methodological concept of research of objects that are systems . General systems theory is closely related to systematic approach and is a concretization and logical-methodological expression of its principles and methods. The first version of the general systems theory was put forward L. von Bertalanffy , however, it had many predecessors (in particular, A.A. Bogdanov ). The general theory of systems arose from Bertalanffy in line with the “organismic” worldview he defended as a generalization of the theory he developed in the 1930s. "the theory of open systems", in which living organisms were considered as systems that constantly exchange matter and energy with the environment. As conceived by Bertalanffy, the general theory of systems was supposed to reflect the significant changes in the conceptual picture of the world that the 20th century brought. For modern science characteristically: 1) its subject is the organization; 2) to analyze this subject, it is necessary to find means of solving problems with many variables (classical science knew problems with only two, at best, with several variables); 3) the place of mechanism is occupied by the understanding of the world as a multitude of heterogeneous and irreducible spheres of reality, the connection between which is manifested in the isomorphism of the laws operating in them; 4) the concept of physicalist reductionism, which reduces all knowledge to the physical, is replaced by the idea of perspectivism - the possibility of building a single science based on the isomorphism of laws in various fields. Within the framework of the general theory of systems, Bertalanffy and his collaborators developed a special apparatus for describing the "behavior" of open systems, based on the formalism of thermodynamics of irreversible processes, in particular, on the apparatus for describing the so-called. equifinal systems (capable of reaching a predetermined end state regardless of the change initial conditions). The behavior of such systems is described by the so-called. teleological equations expressing the characteristics of the behavior of the system at each moment of time as a deviation from the final state, to which the system, as it were, “aspires”.
In the 1950s–70s. a number of other approaches to the construction of a general theory of systems have been proposed (M.Mesarovich, L.Zade, R.Akoff, J.Clear, A.I.Uemov, Yu.A.Urmantsev, R.Kalman, E.Laszlo, etc.). The main attention was paid to the development of the logical-conceptual and mathematical apparatus of system research. In the 1960s (under the influence of criticism, as well as as a result of the intensive development of scientific disciplines close to the general theory of systems) Bertalanffy made refinements to his concept, and in particular distinguished two meanings of the general theory of systems. In a broad sense, it acts as a fundamental science, covering the entire set of problems related to the study and design of systems (the theoretical part of this science includes cybernetics, information theory, game and decision theory, topology, network theory and graph theory, as well as factor analysis) . General systems theory in the narrow sense of general definition system as a complex of interacting elements seeks to derive concepts related to organismic wholes (interaction, centralization, finality, etc.), and applies them to the analysis of specific phenomena. The applied field of general systems theory includes, according to Bertalanffy, systems engineering, operations research, and engineering psychology.
Taking into account the evolution that the understanding of the general theory of systems has undergone in the works of Bertalanffy and others, it can be stated that over time there has been an ever-increasing expansion of the tasks of this concept, with a virtually unchanged state of its apparatus and means. As a result, the following situation has arisen: only the general theory of systems in the narrow sense can be considered a strictly scientific concept (with the corresponding apparatus, means, etc.); as for general systems theory in the broad sense, it either coincides with general systems theory in the narrow sense (in particular, in terms of apparatus), or it is a real extension and generalization of general systems theory in the narrow sense and similar disciplines, but then the question arises about a detailed presentation of its means, methods and apparatus. AT last years Attempts to concrete applications of general systems theory are multiplying, for example, to biology, systems engineering, organization theory, etc.
General systems theory is important for the development of modern science and technology: without replacing special system theories and concepts dealing with the analysis of certain classes of systems, it formulates the general methodological principles of system research.
Literature:
1. General systems theory. M., 1966;
2. Kremyansky V.I. Some features of organisms as "systems" from the point of view of physics, cybernetics and biology. - "VF", 1958, No. 8;
3. Lectorsky V.A., Sadovsky V.N. On the principles of systems research. - "VF", 1960, No. 8;
4. Setrov M.I. Significance of the general theory of systems L. Bertalanffy for biology. - In the book: Philosophical problems of modern biology. M. - L., 1966;
5. Sadovsky V.N. Foundations of the general theory of systems. M., 1974;
6. Blauberg I.V. The issue of integrity and systems approach. M., 1997;
7. Yudin E.G. Methodology of science. Consistency. Activity. M., 1997;
8. Bertalanffy L. Das biologische Weltbild, Bd. 1 Bern, 1949;
9. Idem. Zueiner allgemeinen Systemlehre. – Biology generalis, 1949, S. 114–29;
10. Idem. An Outline of General System Theory. – British Journal Philosophy of Science, 1950, p. 134–65;
11. Idem. Biophysik des Fliessgleichgewichts. Braunschweig, 1953;
12. General Systems, Yearbook of the Society for General Systems Research, eds. L.Bertalanffy and A.Rapoport. Michigan, 1956 (ed. ongoing);
13. Zadeh L.O. The Concept of State in System Theory. – Views on General System Theory, ed. by M.D. Mesarovic. N.Y., 1964.
V.N.Sadovsky
An Austrian biologist living in Canada and the United States, Ludwig von Bertalanffy, first put forward a number of ideas in 1937, which he later combined into one concept. He called it General Systems Theory. What is it? This is the scientific concept of studying various objects considered as a system.
The main idea of the proposed theory was that the laws that govern system objects are the same, the same for different systems. In fairness, it must be said that the main ideas of L. Bertalanffy were laid down by various scientists, including the Russian philosopher, writer, politician, doctor, in his fundamental work "Tectology", written by him in 1912. A.A. Bogdanov actively participated in the revolution, however, in many respects he did not agree with V.I. Lenin. did not accept, but, nevertheless, continued to cooperate with the Bolsheviks, organizing the first Institute of Blood Transfusion in what was then Russia and putting on a medical experiment. He died in 1928. Few people know even today that at the beginning of the twentieth century, the Russian physiologist V.M. Bekhterev, regardless of A.A. Bogdanov, described more than 20 universal laws in the field of psychological and social processes.
General systems theory studies different kinds, the structure of systems, the processes of their functioning and development, the organization of components of structural-hierarchical levels, and much more. L. Bertalanffy also studied the so-called open systems exchanging free energy, matter and information with the environment.
General systems theory currently explores such system-wide regularities and principles as, for example, the hypothesis of semiotic feedback, organizational continuity, compatibility, complementary relationships, the law of necessary diversity, hierarchical compensations, the principle of monocentrism, the least relative resistances, the principle of external complement, the theorem of recursive structures, the law of divergence and others.
Current state systems science owes much to L. Bertalanffy. General systems theory is in many ways similar in terms of goals or research methods to cybernetics - the science of the general laws of the process of managing and transmitting information in different systems(mechanical, biological or social); information theory - a branch of mathematics that defines the concept of information, its laws and properties; game theory, which analyzes with the help of mathematics the competition of two or more opposing forces in order to obtain the greatest gain and the least loss; decision theory, which analyzes rational choices among various alternatives; factor analysis, which uses the procedure for extracting factors in phenomena with many variables.
Today, the general theory of systems is receiving a powerful impetus for its development in synergetics. I. Prigogine and G. Haken investigate non-equilibrium systems, dissipative structures and entropy in open systems. In addition, such applied scientific disciplines as system engineering, the science of system planning, design, evaluation and construction of systems of the “man-machine” type, emerged from the theory of L. Bertalanffy; engineering psychology; field behavior theory operations research - the science of managing the components of economic systems (people, machines, materials, finance, etc.); SMD methodology, which was developed by G.P. Shchedrovitsky, his staff and students; the theory of integral individuality by V. Merlin, which was based largely on the general theory of Bertalanffy systems discussed above.
