Mathematical model of the cognitive structure of the learning space. Cognitive models Cognitive approach to modeling

Individual work

Cognitive modeling

Introduction

1. Concepts and essence of “Cognitive modeling” and “Cognitive map”

2. Problems of the cognitive approach

Conclusion

List of used literature

INTRODUCTION

In the mid-17th century, the famous philosopher and mathematician René Descartes expressed an aphorism that has become classic: “Cogito Ergo Sum” (I think, therefore I am). The Latin root cognito has an interesting etymology. It consists of the parts “co-“ (“together”) + “gnoscere” (“know”). In English there is a whole family of terms with this root: “cognition”, “cognize”, etc.

In the tradition that we denote by the term “cognitive”, only one “face” of thought is visible - its analytical essence (the ability to decompose the whole into parts), to decompose and reduce reality. This side of thinking is associated with identifying cause-and-effect relationships (causality), which is characteristic of reason. Apparently, Descartes absolutized reason in his algebraic system. Another “face” of thought is its synthesizing essence (the ability to construct a whole from an unbiased whole), perceive the reality of intuitive forms, synthesize solutions and anticipate events. This side of thinking, revealed in the philosophy of Plato and his school, is inherent in the human mind. It is no coincidence that in Latin roots we find two foundations: ratio (rational relations) and reason (reasonable insight into the essence of things). The rational face of thought originates from the Latin reri ("to think"), which goes back to the Old Latin root ars (art), then turned into the modern concept of art. Thus, reason (reasonable) is a thought akin to the artist’s creativity. Cognition as "mind" means "the ability to think, explain, justify actions, ideas and hypotheses."

For “strong” cognition, the special, constructive status of the category “hypothesis” is essential. It is the hypothesis that is the intuitive starting point for deducing the solution image. When considering the situation, the decision maker discovers in the situation some negative links and structures (“gaps” of the situation), which must be replaced with new objects, processes and relationships that eliminate the negative impact and create a clearly expressed positive effect. This is the essence of innovation management. In parallel with the detection of “gaps” in the situation, often qualified as “challenges” or even “threats,” the control subject intuitively imagines some “positive responses” as holistic images of the state of the future (harmonized) situation.

Cognitive analysis and modeling are fundamentally new elements in the structure of decision support systems.

Cognitive modeling technology allows you to explore problems with unclear factors and relationships; - take into account changes in the external environment; - use objectively established trends in the development of the situation in your interests.

Such technologies are gaining more and more confidence among structures involved in strategic and operational planning at all levels and in all areas of management. The use of cognitive technologies in the economic sphere makes it possible to quickly develop and justify a strategy for the economic development of an enterprise, bank, region or an entire state, taking into account the impact of changes in the external environment. In the field of finance and the stock market, cognitive technologies make it possible to take into account the expectations of market participants. In the military field and the field of information security, the use of cognitive analysis and modeling makes it possible to counter strategic information weapons and recognize conflict structures without bringing the conflict to the stage of an armed conflict.

1. Concepts and essence of “Cognitive modeling” and “Cognitive map”

Cognitive modeling methodology for analyzing and making decisions in ill-defined situations was proposed by Axelrod. It is based on modeling the subjective ideas of experts about the situation and includes: methodology for structuring the situation: a model for representing the expert’s knowledge in the form of a signed digraph (cognitive map) (F, W), where F is the set of factors of the situation, W is the set of cause-and-effect relationships between factors situations; methods of situation analysis. Currently, the methodology of cognitive modeling is developing in the direction of improving the apparatus for analyzing and modeling the situation. Models for forecasting the development of the situation are proposed here; methods for solving inverse problems

A cognitive map (from Latin cognitio - knowledge, cognition) is an image of a familiar spatial environment.

Cognitive maps are created and modified as a result of the active interaction of the subject with the outside world. In this case, cognitive maps of varying degrees of generality, “scale” and organization can be formed (for example, an overview map or a path map, depending on the completeness of the representation of spatial relationships and the presence of an expressed point of reference). This is a subjective picture that has, first of all, spatial coordinates in which individual perceived objects are localized. There is a path map as a sequential representation of connections between objects along a specific route, and an overview map as a simultaneous representation of the spatial location of objects.

The leading scientific organization in Russia engaged in the development and application of cognitive analysis technology is the Institute of Management Problems of the Russian Academy of Sciences, division: Sector-51, scientists Maksimov V.I., Kornoushenko E.K., Kachaev S.V., Grigoryan A.K. and others. This lecture is based on their scientific work in the field of cognitive analysis.

The technology of cognitive analysis and modeling (Figure 1) is based on the cognitive (cognitive-target) structuring of knowledge about an object and its external environment.

Figure 1. Technology of cognitive analysis and modeling

Cognitive structuring of a subject area is the identification of future target and undesirable states of a control object and the most significant (basic) factors of control and the external environment that influence the transition of the object to these states, as well as the establishment at a qualitative level of cause-and-effect relationships between them, taking into account mutual influence factors on each other.

The results of cognitive structuring are displayed using a cognitive map (model).

2. Cognitive (cognitive-target) structuring of knowledge about the object under study and its external environment based on PEST analysis and SWOT analysis

The selection of basic factors is carried out by applying PEST analysis, which identifies four main groups of factors (aspects) that determine the behavior of the object under study (Figure 2):

P olicy - politics;

E economy - economy;

S ociety - society (sociocultural aspect);

T echnology - technology

Figure 2. PEST analysis factors

For each specific complex object there is its own special set of the most significant factors that determine its behavior and development.

PEST analysis can be considered as a variant of system analysis, since factors related to the listed four aspects are, in general, closely interrelated and characterize various hierarchical levels of society as systems.

This system has determinative connections directed from the lower levels of the system hierarchy to the upper ones (science and technology influences the economy, the economy influences politics), as well as reverse and inter-level connections. A change in any of the factors through this system of connections can influence all the others.

These changes may pose a threat to the development of the object, or, conversely, provide new opportunities for its successful development.

The next step is a situational analysis of problems, SWOT analysis (Figure 3):

S trengths - strengths;

W eaknesses - shortcomings, weaknesses;

O pportunities - opportunities;

T hreats - threats.

Figure 3. SWOT analysis factors

It includes an analysis of the strengths and weaknesses of the development of the object under study in their interaction with threats and opportunities and allows us to identify current problem areas, bottlenecks, chances and dangers, taking into account environmental factors.

Opportunities are defined as circumstances conducive to the favorable development of an object.

Threats are situations in which damage to an object may be caused, for example, its functioning may be disrupted or it may lose its existing advantages.

Based on the analysis of various possible combinations of strengths and weaknesses with threats and opportunities, the problem field of the object under study is formed.

The problem field is a set of problems that exist in the modeled object and the environment, in their relationship with each other.

The availability of such information is the basis for determining development goals (directions) and ways to achieve them, and developing a development strategy.

Cognitive modeling based on the conducted situational analysis makes it possible to prepare alternative solutions to reduce the degree of risk in identified problem areas, to predict possible events that may have the most serious impact on the position of the modeled object.

The stages of cognitive technology and their results are presented in Table 1:

Table 1

Stages of cognitive technology and results of its application

Stage name	Result presentation form
1. Cognitive (cognitive-target) structuring of knowledge about the object under study and its external environment based on PEST analysis and SWOT analysis: Analysis of the initial situation around the object under study, highlighting the basic factors characterizing economic, political and other processes occurring in the object and in its macroenvironment and influencing the development of the object. 1.1 Identification of factors characterizing the strengths and weaknesses of the object under study 1.2 Identification of factors characterizing opportunities and threats from the external environment of the object 1.3 Construction of the problem field of the object under study	Report on a systemic conceptual study of an object and its problem area
2. Construction of a cognitive model of object development - formalization of knowledge obtained at the stage of cognitive structuring 2.1 Identification and justification of factors 2.2 Establishment and justification of relationships between factors 2.3 Construction of a graph model	Computer cognitive model of an object in the form of a directed graph (and matrix of factor relationships)
3. Scenario study of trends in the development of the situation around the object under study (with the support of the software systems "SITUATION", "COMPASS", "KIT") 3.1 Determining the purpose of the study 3.2 Setting research scenarios and modeling them 3.3 Identification of development trends of an object in its macroenvironment 3.4 Interpretation of scenario study results	Report on the scenario study of the situation, with interpretation and conclusions
4. Development of strategies for managing the situation around the object under study 4.1 Definition and justification of the management goal 4.2 Solving the inverse problem 4.3 Selection of management strategies and ordering them according to criteria: possibility of achieving the goal; risk of losing control of the situation; emergency risk	Report on the development of management strategies with justification of strategies according to various criteria of management quality
5. Search and justification of strategies for achieving goals in stable or changing situations For stable situations: a) selection and justification of the management goal; b) selection of activities (controls) to achieve the goal; c) analysis of the fundamental possibility of achieving the goal from the current state of the situation using selected activities; d) analysis of real restrictions on the implementation of selected activities; e) analysis and justification of the real possibility of achieving the goal; f) development and comparison of strategies for achieving the goal by: proximity of management results to the intended goal; costs (financial, physical, etc.); by the nature of the consequences (reversible, irreversible) from the implementation of these strategies in a real situation; on the risk of emergency situations For changing situations: a) selection and justification of the current management goal; b) in relation to the current goal, the previous paragraphs b-f are valid; c) analysis of changes occurring in the situation and their display in a graph model of the situation. Go to point a.	Report on the development of strategies for achieving goals in stable or changing situations
6. Development of a program for implementing the development strategy of the object under study based on dynamic simulation modeling (with the support of the Ithink software package) 6.1. Distribution of resources by area and over time 6.2 Coordination 6.3 Monitoring of execution	Program for implementing the site development strategy. Computer simulation model of object development

2. Problems of the cognitive approach

Today, many advanced countries are “promoting” an economy based on knowledge and effective management. Intellectual property becomes the most valuable commodity of the state. The essence of modern and future war is the confrontation between intellectuals. In such conditions, the most appropriate ways to achieve geopolitical goals are indirect and unconventional actions and, therefore, information weapons acquire enormous significance. There are two concepts for the development of strategic weapons with different roles for Strategic Information Weapons (SIW) in them. The first generation SIO is an integral part of strategic weapons along with other types of strategic weapons and conventional weapons.

The second generation SIO is an independent, radically new type of strategic weapon that emerged as a result of the information revolution and is used in new strategic areas (for example, economic, political, ideological, etc.). The duration of exposure to such weapons can be much longer - a month, a year or more. The second generation SIO will be capable of countering many other types of strategic weapons and will form the core of strategic weapons. The situations emerging as a result of the application of SIO-2 pose a threat to Russia's security and are characterized by uncertainty, an unclear and fuzzy structure, the influence of a large number of heterogeneous factors and the presence of many alternative development options. This leads to the need to apply non-traditional methods that make it possible to study geopolitical, information and other processes occurring in Russia and the world, in the aggregate and in interaction both with each other and with the external unstable environment. Cognitive modeling is intended for structuring, analysis and making management decisions in complex and uncertain situations (geopolitical, internal political, military, etc.), in the absence of quantitative or statistical information about the processes taking place in such situations.

Cognitive modeling allows in express mode

in a short time at a high quality level:

- assess the situation and analyze the mutual influence of existing factors that determine possible scenarios for the development of the situation;

- identify trends in the development of situations and the real intentions of their participants;

- develop a strategy for using trends in the development of the political situation in the national interests of Russia;

- determine possible mechanisms of interaction between participants in the situation to achieve its targeted development in the interests of Russia;

- develop and justify directions for managing the situation in the interests of Russia;

- identify possible options for the development of the situation, taking into account the consequences of making the most important decisions and compare them.

The use of cognitive modeling technology allows you to act proactively and not turn potentially dangerous situations into threatening and conflict situations, and if they arise, make rational decisions in the interests of the constituent entities of Russia.

For tasks related to organizational systems, the problem of uncertainty in describing and modeling the functions of participants is not methodological, but inherent in the very subject of research. Various formulations of the problem of managing the situation are possible depending on the completeness of the information available to the participants about the situation and about the other participants, in particular to search for resonance and synergistic effects, when the improvement of the situation with the simultaneous influence of several participants on it is greater than the “combination” of positive effects from each of the participants separately.

From the point of view of management science, today it is especially important to use soft resonant management of complex socio-economic systems, the art of which lies in the methods of self-government and self-control of systems. Weak, so-called resonance phenomena, are extremely effective for “promotion” or self-government, since they correspond to the internal trends in the development of complex systems. The main problem is how to push the system onto one of its own and favorable development paths with a small resonant effect, how to ensure self-government and self-sustaining development (self-promotion).

Conclusion

The use of cognitive modeling opens up new possibilities for forecasting and management in various areas:

in the economic sphere, this allows you to quickly develop and justify a strategy for the economic development of an enterprise, bank, region or even an entire state, taking into account the impact of changes in the external environment;

in the field of finance and the stock market - take into account the expectations of market participants;

in the military field and the field of information security - to counter strategic information weapons, recognizing conflict structures in advance and developing adequate measures to respond to threats.

Cognitive modeling automates some of the functions of cognitive processes, so they can be successfully used in all areas in which self-knowledge is in demand. Here are just a few of these areas:

1. Models and methods of intelligent information technologies and systems for creating geopolitical, national and regional strategies for socio-economic development.

2. Models of survival of “soft” systems in changing environments with scarce resources.

3. Situational analysis and management of developments in crisis environments and situations.

4. Information monitoring of socio-political, socio-economic and military-political situations.

5. Development of principles and methodology for conducting computer analysis of problem situations.

6. Development of analytical scenarios for the development of problem situations and their management.

8. Monitoring problems in the socio-economic development of a corporation, region, city, state.

9. Technology of cognitive modeling of targeted development of the Russian Federation region.

10. Analysis of the development of the region and monitoring of problematic situations in the targeted development of the region.

11. Models for the formation of state regulation and self-regulation of the consumer market.

12. Analysis and management of the development of the situation in the consumer market.

Cognitive modeling technology can be widely used for unique development projects of regions, banks, corporations (and other objects) in crisis conditions after appropriate training.

List of used literature

1. http://www.ipu.ru

2. http://www.admhmao.ru

3. Maksimov V.I., Kornoushenko E.K. Knowledge is the basis of analysis. Banking technologies, No. 4, 1997.

4. Maksimov V.I., Kornoushenko E.K. Analytical basis for applying the cognitive approach to solving semi-structured problems. Proceedings of IPU, issue 2, 1998.

5. Maksimov V.I., Kachaev S.V., Kornoushenko E.K. Conceptual modeling and monitoring of problem and conflict situations in the targeted development of the region. On Sat. "Modern management technologies for city and regional administrations." Foundation "Problems of Management", M. 1998.

Cognitive modeling

Introduction

1. Concepts and essence of “Cognitive modeling” and “Cognitive map”

2. Problems of the cognitive approach

Conclusion

List of used literature

INTRODUCTION

Cognitive analysis and modeling are fundamentally new elements in the structure of decision support systems.

1. Concepts and essence of “Cognitive modeling” and “Cognitive map”

A cognitive map (from Latin cognitio - knowledge, cognition) is an image of a familiar spatial environment.

The technology of cognitive analysis and modeling (Figure 1) is based on the cognitive (cognitive-target) structuring of knowledge about an object and its external environment.

Figure 1. Technology of cognitive analysis and modeling

The results of cognitive structuring are displayed using a cognitive map (model).

2. Cognitive (cognitive-target) structuring of knowledge about the object under study and its external environment based on PEST analysis and SWOT analysis

The selection of basic factors is carried out by applying PEST analysis, which identifies four main groups of factors (aspects) that determine the behavior of the object under study (Figure 2):

P olicy - politics;

E economy - economy;

S ociety - society (sociocultural aspect);

T echnology - technology

Figure 2. PEST analysis factors

For each specific complex object there is its own special set of the most significant factors that determine its behavior and development.

These changes may pose a threat to the development of the object, or, conversely, provide new opportunities for its successful development.

The next step is a situational analysis of problems, SWOT analysis (Figure 3):

S trengths - strengths;

W eaknesses - shortcomings, weaknesses;

O pportunities - opportunities;

T hreats - threats.

Figure 3. SWOT analysis factors

Opportunities are defined as circumstances conducive to the favorable development of an object.

Threats are situations in which damage to an object may be caused, for example, its functioning may be disrupted or it may lose its existing advantages.

Based on the analysis of various possible combinations of strengths and weaknesses with threats and opportunities, the problem field of the object under study is formed.

The problem field is a set of problems that exist in the modeled object and the environment, in their relationship with each other.

The availability of such information is the basis for determining development goals (directions) and ways to achieve them, and developing a development strategy.

COGNITIVE SIMULATION

CONTENT
Introduction
1. Subject of cognitive analysis
1.1. External environment
1.2. Instability of the external environment
1.3. Poorly structured external environment
2. General concept of cognitive analysis
3. Stages of cognitive analysis
4. Goals, stages and basic concepts of cognitive modeling
4. 1. The purpose of building a cognitive model
4.2. Stages of cognitive modeling
4.3. Directed graph (cognitive map)
4.4. Functional graph (completing the construction of a cognitive model)
5. Types of factors

6.1.Identification of factors (elements of the system)
6.2. Two approaches to identifying relationships between factors
6.3.Examples of identifying factors and connections between them
6.4. The problem of determining the strength of influence of factors
7. Checking the adequacy of the model
8. Using a cognitive model
8.1. Application of cognitive models in decision support systems
8.2. An example of working with a cognitive model
9. Computer systems to support management decisions
9.1. General characteristics of decision support systems
9.2. "Situation - 2"
9.3. "Compass-2"
9.4. "Canvas"
Conclusion
Bibliography
Application

Introduction
Currently, obtaining reliable information and its rapid analysis have become the most important prerequisites for successful management. This is especially true if the control object and its external environment are a complex of complex processes and factors that significantly influence each other.
One of the most productive solutions to problems arising in the field of management and organization is the use of cognitive analysis, which is the subject of study in the course work.
The cognitive modeling methodology, intended for analysis and decision-making in poorly defined situations, was proposed by the American researcher R. Axelrod 1.
Initially, cognitive analysis was formed within the framework of social psychology, namely, cognitivism, which studies the processes of perception and cognition.
The application of the developments of social psychology in management theory led to the formation of a special branch of knowledge - cognitive science, concentrating on the study of problems of management and decision making.
Now the methodology of cognitive modeling is developing in the direction of improving the apparatus for analyzing and modeling situations.
The theoretical achievements of cognitive analysis became the basis for the creation of computer systems aimed at solving applied problems in the field of management.
Work on the development of the cognitive approach and its application to the analysis and control of so-called semi-structured systems is currently being carried out at the Institute of Control Problems of the Russian Academy of Sciences 2 .
By order of the Administration of the President of the Russian Federation, the Government of the Russian Federation, and the Government of the City of Moscow, a number of socio-economic studies using cognitive technology were carried out at the IPU RAS. The recommendations developed are successfully applied by the relevant ministries and departments 3 .
Since 2001, under the auspices of the IPU RAS, international conferences “Cognitive Analysis and Management of Situation Development (CASC)” have been regularly held.
When writing the course work, the works of domestic researchers were involved - A.A. Kulinich, D.I. Makarenko, S.V. Kachaeva, V.I. Maksimova, E.K. Kornoushenko, E. Grebenyuk, G.S. Osipova, A. Raikova. Most of the named researchers are specialists from the IPU RAS.
Thus, cognitive analysis is being quite actively developed not only by foreign, but also by domestic specialists. However, within the framework of cognitive science, a number of problems remain, the solution of which could significantly improve the results of applied developments based on cognitive analysis.
The purpose of the course work is to analyze the theoretical basis of cognitive technologies, problems of the methodology of cognitive analysis, as well as computer decision support systems based on cognitive modeling.
The structure of the work corresponds to the set goals, which consistently reveals the basic concepts and stages of cognitive analysis in general, cognitive modeling (as a key point of cognitive analysis), general principles of applying the cognitive approach in practice in the field of management, as well as computer technologies that apply methods of cognitive analysis.

1. Subject of cognitive analysis
1.1. External environment
For effective management, forecasting and planning, an analysis of the external environment in which management objects operate is required.
The external environment is usually defined by researchers as a set of economic, social and political factors and entities that have a direct or indirect impact on the ability and ability of the entity (be it a bank, an enterprise, any other organization, an entire region, etc.) to achieve its development goals.
To navigate the external environment and analyze it, it is necessary to clearly understand its properties. Experts from the Institute of Management Problems of the Russian Academy of Sciences identify the following main characteristics of the external environment:
1. Complexity - this refers to the number and variety of factors to which the subject must respond.
2. The relationship of factors, that is, the force with which a change in one factor affects changes in other factors.
3. Mobility - the speed with which changes occur in the external environment 4.
The identification of these types of characteristics to describe the environment indicates that researchers apply a systems approach and consider the external environment as a system or a set of systems. It is within the framework of this approach that it is customary to represent any objects in the form of a structured system, to highlight the elements of the system, the relationships between them and the dynamics of development of the elements, relationships and the entire system as a whole. Therefore, cognitive analysis, used to study the external environment and develop ways and methods of functioning in it, is sometimes considered as a component of systems analysis 5 .
The specificity of the external environment of control objects is that this environment is subject to the influence of the human factor. In other words, it includes subjects endowed with autonomous will, interests and subjective ideas. This means that this environment does not always obey linear laws that unambiguously describe the relationship of causes and effects.
This implies two basic parameters of the external environment in which the human factor operates - instability and weak structure. Let's take a closer look at these parameters.

1.2. Instability of the external environment

The instability of the external environment is often identified by researchers with unpredictability. “The degree of instability of the economic and political environment external to... [the object of management] is characterized by the familiarity of expected events, the expected pace of change, and the ability to predict the future” 6 . This unpredictability is generated by multifactoriality, variability of factors, pace and direction of development of the environment.
“The combined effect of all environmental factors, summarize V. Maksimov, S. Kachaev and E. Kornoushenko, forms the level of its instability and determines the feasibility and direction of surgical intervention in ongoing processes” 7 .
The higher the instability of the external environment, the more difficult it is to develop adequate strategic decisions. Therefore, there is an objective need to assess the degree of instability of the environment, as well as to develop approaches to its analysis.
According to I. Ansoff, the choice of strategy for managing and analyzing situations depends on the level of instability of the external environment. With moderate instability, conventional control is applied based on extrapolation of knowledge about the past of the environment. At an average level of instability, management is carried out on the basis of a forecast of changes in the environment (for example, “technical” analysis of financial markets). At a high level of instability, management is used based on flexible expert decisions (for example, “fundamental” 8 analysis of financial markets) 9 .

1.3. Poorly structured external environment

The environment in which management subjects are forced to work is characterized not only as unstable, but also as poorly structured. These two characteristics are strongly interrelated, but different. However, sometimes these terms are used as synonyms.
Thus, specialists from the Institute of Control Sciences of the Russian Academy of Sciences, when defining weakly structured systems, point out some of their properties that are also inherent in unstable systems: “The difficulties of analyzing processes and making management decisions in such areas as economics, sociology, ecology, etc. are caused by a number of features inherent in these areas, namely: the multifaceted nature of the processes occurring in them (economic, social, etc.) and their interconnectedness; due to this, it is impossible to isolate and conduct a detailed study of individual phenomena - all phenomena occurring in them must be considered in their entirety; the lack of sufficient quantitative information about the dynamics of processes, which forces us to move to a qualitative analysis of such processes; variability of the nature of processes over time, etc. Due to these features, economic, social, etc. systems are called weakly structured systems” 10.
However, it should be noted that the term “instability” implies the impossibility or difficulty of predicting the development of a system, and weak structure implies the impossibility of formalizing it. Ultimately, the characteristics “instability” and “weakly structured”, in my opinion, reflect different aspects of the same phenomenon, since we traditionally perceive a system that we cannot formalize and thus absolutely accurately predict its development (that is, a weakly structured system) , as unstable, prone to chaos. Therefore, here and further, following the authors of the studied articles, I will use these terms as equivalent. Sometimes researchers, along with the above concepts, use the term “complex situations”.
So, in contrast to technical systems, economic, socio-political and other similar systems are characterized by the absence of a detailed quantitative description of the processes occurring in them - the information here is of a qualitative nature. Therefore, for weakly structured systems it is impossible to create formal traditional quantitative models. Systems of this type are characterized by uncertainty, description at a qualitative level, and ambiguity in assessing the consequences of certain decisions 11 .
Thus, the analysis of an unstable external environment (weakly structured systems) is fraught with many difficulties. When solving them, you need the intuition of an expert, his experience, associative thinking, and guesses.
Computer tools for cognitive modeling of situations make it possible to cope with such an analysis. These tools have been used in economically developed countries for decades, helping enterprises to survive and develop their businesses, and authorities to prepare effective regulations 12 . Cognitive modeling is designed to help the expert reflect at a deeper level and organize his knowledge, as well as formalize his ideas about the situation to the extent possible.

2. General concept of cognitive analysis

Cognitive analysis is sometimes referred to by researchers as “cognitive structuring” 13 .
Cognitive analysis is considered one of the most powerful tools for studying an unstable and poorly structured environment. It contributes to a better understanding of the problems existing in the environment, identification of contradictions and a qualitative analysis of ongoing processes. The essence of cognitive (cognitive) modeling - the key point of cognitive analysis - is to reflect the most complex problems and trends in the development of a system in a simplified form in a model, to explore possible scenarios for the emergence of crisis situations, to find ways and conditions for their resolution in a model situation. The use of cognitive models qualitatively increases the validity of management decisions in a complex and rapidly changing environment, relieves the expert from “intuitive wandering”, and saves time on understanding and interpreting events occurring in the system 14 .
IN AND. Maksimov and S.V. Kachaev, to explain the principles of using information cognitive technologies to improve management, uses the metaphor of a ship in a stormy ocean - the so-called “frigate-ocean” model. Most commercial and non-profit activities in unstable and poorly structured environments “inevitably involve risk, arising both from the uncertainty of future operating conditions and from the possibility of erroneous decisions made by management…. It is very important for management to be able to anticipate such difficulties and develop strategies to overcome them in advance, i.e. have pre-developed guidelines for possible behavior.” These developments are proposed to be carried out on models in which the information model of the control object (“frigate”) interacts with a model of the external environment - economic, social, political, etc. ("ocean"). “The purpose of such modeling is to give recommendations to the “frigate” on how to cross the “ocean” with the least “effort”... Of interest... are ways to achieve the goal, taking into account favorable “winds” and “currents”... So, we set the goal: to determine the “wind rose”... [ external environment], and then we’ll see which “winds” will be tailwinds, which will be counterwinds, how to use them and how to discover the properties of the external situation that are important for... [the object]” 15 .
Thus, the essence of the cognitive approach is, as already mentioned, to help the expert reflect on the situation and develop the most effective management strategy, based not so much on his intuition, but on ordered and verified (as far as possible) knowledge about a complex system. Examples of using cognitive analysis to solve specific problems will be discussed below in paragraph “8. Using a Cognitive Model."

3. Stages of cognitive analysis

Cognitive analysis consists of several stages, at each of which a specific task is implemented. The consistent solution of these problems leads to the achievement of the main goal of cognitive analysis. Researchers give different nomenclature of stages depending on the specifics of the object(s) being studied 16 . If we summarize and generalize all these approaches, we can identify the following stages that are characteristic of the cognitive analysis of any situation.

(As a result of passing stages 3 – 5, a cognitive model of the situation (system) is ultimately built, which is displayed in the form of a functional graph. Therefore, we can say that stages 3 – 5 represent cognitive modeling. In more detail, all these stages and basic concepts cognitive modeling will be discussed in paragraphs 4 – 7).

Let us consider in detail each of the above stages (with the exception of the first and second, which are essentially preparatory), the mechanisms for implementing the particular tasks of each stage, as well as the problems that arise at different stages of cognitive analysis.

4. Goals, stages and basic concepts of cognitive modeling

The key element of cognitive analysis is the construction of a cognitive model.

4. 1. The purpose of building a cognitive model

Cognitive modeling contributes to a better understanding of the problem situation, identification of contradictions and qualitative analysis of the system. The purpose of modeling is to form and clarify a hypothesis about the functioning of the object under study, considered as a complex system that consists of separate, but still interconnected elements and subsystems. In order to understand and analyze the behavior of a complex system, a structural diagram of the cause-and-effect relationships of the system elements is built. Analysis of these connections is necessary for the implementation of various process controls in the system 18.

4.2. Stages of cognitive modeling

In general terms, the stages of cognitive modeling are discussed above. The works of specialists from the IPU RAS contain a detailed description of these stages. Let us highlight the main ones.

Thus, the cognitive model includes a cognitive map (directed graph) and weights of graph arcs (assessment of mutual influence or influence of factors). When determining the weights of the arcs, the directed graph turns into a functional one.
Problems of identifying factors, assessing the mutual influence of factors and typology of factors will be discussed in paragraphs 5 and 6; Here we will consider such basic concepts of cognitive modeling as a cognitive map and a functional graph.

4.3. Directed graph (cognitive map)

Within the framework of the cognitive approach, the terms “cognitive map” and “directed graph” are often used interchangeably; although, strictly speaking, the concept of a directed graph is broader, and the term “cognitive map” indicates only one of the applications of a directed graph.
A cognitive map consists of factors (elements of the system) and connections between them.
In order to understand and analyze the behavior of a complex system, a structural diagram of cause-and-effect relationships of system elements (situation factors) is constructed. Two elements of the system A and B are depicted on the diagram as separate points (vertices) connected by an oriented arc, if element A is connected to element B by a cause-and-effect relationship: A a B, where: A is the cause, B is the effect.
Factors can influence each other, and such influence, as already indicated, can be positive, when an increase (decrease) in one factor leads to an increase (decrease) in another factor, and negative, when an increase (decrease) in one factor leads to a decrease (increase). ) another factor 20 . Moreover, the influence may also have a variable sign depending on possible additional conditions.
Similar schemes for representing cause-and-effect relationships are widely used to analyze complex systems in economics and sociology.
An example of a cognitive map of some economic situation is shown in Fig. 1.

Figure 1. Directed graph 21.

4.4. Functional graph (completing the construction of a cognitive model)
A cognitive map reflects only the fact that factors influence each other. It does not reflect the detailed nature of these influences, nor the dynamics of changes in influences depending on changes in the situation, nor temporary changes in the factors themselves. Taking into account all these circumstances requires a transition to the next level of information structuring, that is, to a cognitive model.
At this level, each connection between the factors of the cognitive map is revealed by corresponding dependencies, each of which can contain both quantitative (measurable) variables and qualitative (non-measured) variables. In this case, quantitative variables are presented naturally in the form of their numerical values. Each qualitative variable is associated with a set of linguistic variables that reflect the different states of this qualitative variable (for example, consumer demand can be “weak”, “moderate”, “exciting”, etc.), and each linguistic variable corresponds to a certain numerical equivalent in scale. As knowledge accumulates about the processes occurring in the situation under study, it becomes possible to reveal in more detail the nature of the connections between factors.
Formally, a cognitive model of a situation can, like a cognitive map, be represented by a graph, but each arc in this graph already represents a certain functional relationship between the corresponding factors; those. the cognitive model of the situation is represented by a functional graph 22.
An example of a functional graph reflecting the situation in a conditional region is presented in Fig. 2.

Figure 2. Functional graph 23.
Note that this model is a demonstration model, so many environmental factors are not taken into account.

5. Types of factors
To structure a situation (system), researchers divide factors (elements) into various groups, each of which has certain specifics, namely a functional role in modeling. Moreover, depending on the specifics of the analyzed situation (system), the typology of factors (elements) may be different. Here I will highlight some types of factors used in cognitive modeling of most systems (situations, environments).
Firstly, among all the detected factors, basic factors (those that significantly influence the situation and describe the essence of the problem) and “redundant” (insignificant) factors that are “weakly connected” with the “core” of basic factors 24 are distinguished.
When analyzing a specific situation, an expert usually knows or assumes what changes in basic factors are desirable for him. The factors of greatest interest to the expert are called target factors. IN AND. Maksimov, E.K. Kornoushenko, S.V. Kachaev describes the target factors as follows: “These are the “output” factors of the cognitive model. The task of developing solutions for managing processes in a situation is to ensure the desired changes in target factors; this is the goal of management. A goal is considered correctly set if desirable changes in some target factors do not lead to undesirable changes in other target factors” 25.
In the initial set of basic factors, a set of so-called control factors is identified - “input” factors of the cognitive model, through which control influences are supplied to the model. A control action is considered consistent with the goal if it does not cause undesirable changes in any of the target factors” 26. To identify control factors, factors influencing the target ones are determined. The control factors in the model will be potential levers of influence on the situation 27 .
The influence of control factors is summarized in the concept of “vector of control actions” - a set of factors, each of which is supplied with a control pulse of a given value 28 .
Factors of the situation (or elements of the system) can also be divided into internal (belonging to the control object itself and under more or less complete control of management) and external (reflecting the impact on the situation or system of external forces that may not be controlled or only indirectly controlled by the subject of control) .
External factors are usually divided into predictable ones, the occurrence and behavior of which can be predicted based on the analysis of available information, and unpredictable ones, the behavior of which an expert learns about only after their occurrence 29 .
Sometimes researchers identify so-called indicator factors that reflect and explain the development of processes in a problem situation (system, environment) 30 . For similar purposes, the concept of integral indicators (factors) is also used, by changes in which one can judge general trends in this area 31 .
Factors are also characterized by a tendency to change their values. The following trends are distinguished: growth, decline. If there is no change in the factor, it is said that there is no trend or a zero trend 32 .
Finally, it should be noted that it is possible to identify causal factors and effect factors, short-term and long-term factors.

6. Main problems of constructing a cognitive model
There are two main problems in constructing a cognitive model.
Firstly, difficulties are caused by identifying factors (elements of the system) and ranking factors (selecting basic and secondary ones) (at the stage of constructing a directed graph).
Secondly, identifying the degree of mutual influence of factors (determining the weights of the graph arcs) (at the stage of constructing a functional graph).

6.1. Identification of factors (elements of the system)

It can be stated that researchers have not developed a clear algorithm for identifying the elements of the systems under study. It is assumed that the situation factors being studied are already known to the expert conducting the cognitive analysis.
Usually, when considering large (for example, macroeconomic) systems, the so-called PEST analysis is used (Policy - politics, Economy - economics, Society - society, Technology - technology), which involves identifying 4 main groups of factors through which political, economic, sociocultural and technological aspects of the environment 33. This approach is well known in all socio-economic sciences.
PEST analysis is a tool for the historically established four-element strategic analysis of the external environment. Moreover, for each specific complex object there is its own special set of key factors that directly and most significantly affect the object. The analysis of each of the identified aspects is carried out systematically, since in life all these aspects are closely interconnected 34 .
In addition, it is assumed that the expert can judge the nomenclature of factors in accordance with his subjective ideas. Thus, “Fundamental” analysis of financial situations, close in some parameters to cognitive analysis, is based on a set of basic factors (financial and economic indicators) - both macroeconomic and lower order, both long-term and short-term. These factors, in accordance with the “fundamental” approach, are determined on the basis of common sense 35.
Thus, the only conclusion that can be drawn regarding the process of identifying factors is that the analyst, in pursuit of this goal, must be guided by ready-made knowledge of various socio-economic sciences involved in the specific study of various systems, as well as his experience and intuition.

6.2. Two approaches to identifying relationships between factors

To reflect the nature of the interaction of factors, positive and normative approaches are used.
The positive approach is based on taking into account the objective nature of the interaction of factors and allows us to draw arcs, assign signs (+ / -) and exact weights to them, that is, reflect the nature of this interaction. This approach is applicable if the relationship between factors can be formalized and expressed by mathematical formulas that establish precise quantitative relationships.
However, not all real systems and their subsystems are described by one or another mathematical formula. We can say that only some special cases of interaction of factors have been formalized. Moreover, the more complex the system, the less likely it is to be fully described using traditional mathematical models. This is primarily due to the fundamental properties of unstable, weakly structured systems described in paragraph 1. Therefore, the positive approach is complemented by the normative one.
The normative approach is based on a subjective, evaluative perception of the interaction of factors, and its use also makes it possible to assign weights to the arcs, i.e., reflect the strength (intensity) of the interaction of factors. Determining the influence of factors on each other and assessing these influences are based on the expert’s “estimates” and are expressed quantitatively using the [-1,1] scale or linguistic variables such as “strong”, “weak”, “moderate” 36. In other words, with a normative approach, the expert is faced with the task of intuitively determining the strength of the mutual influence of factors, based on his knowledge of the qualitative relationship.
In addition, as already mentioned, the expert needs to determine the negative or positive nature of the influence of the factors, and not just the strength of the influence. When carrying out this task, it is obviously possible to use the two approaches mentioned above.

6.3.Examples of identifying factors and connections between them
Let us give some examples used by researchers to illustrate the identification of factors and the establishment of connections between them.
Thus, V. Maksimov, S. Kachaev and E. Kornoushenko, to build a cognitive model of the processes occurring in a crisis economy, identify the following basic factors: 1. Gross domestic product (GDP); 2. Aggregate demand; 3. Inflation; 4. Savings; 5. Consumption; 6. Investments; 7. Government procurement; 8. Unemployment; 9. Supply of money; 10. Government transfer payments; 11. Government expenditures; 12. Government revenues; 13. State budget deficit; 14. Taxes; 15. Non-payment of taxes; 16. Interest rate; 17. Demand for money 37.
V. Maksimov, E. Grebenyuk, E. Kornoushenko in the article “Fundamental and technical analysis: integration of two approaches” give another example of identifying factors and reveal the nature of the connections between them: “The most important economic indicators that influence the stock market in the USA and Europe are are: gross national product (GNP), industrial output index (PPI), consumer price index (CPI), producer price index (PPI), unemployment rate, oil price, dollar exchange rate... If the market is growing and economic indicators confirm stable economic development , then we can expect a further rise in prices... Shares rise in price if the company's profits are growing and there is a prospect for their further growth... If the actual growth rates of economic indicators diverge from the expected ones, this leads to panic in the stock market and its sharp changes. The change in gross national product is normally 3-5% per year. If the annual growth of GNP exceeds 5%, then this is called an economic boom, which can ultimately lead to a market crash. Changes in GNP can be predicted by changes in the manufacturing industry index. A sharp increase in the IPI indicates a possible increase in inflation, which leads to a fall in the market. An increase in the CPI and PPI and oil prices also leads to a fall in the market. High unemployment rates in the United States and Europe (over 6%) force federal agencies to lower the bank interest rate, which leads to a revival of the economy and a rise in stock prices. If unemployment decreases gradually, the market does not react to these changes. If its level drops sharply and becomes less than the expected value, then the market begins to fall, because a sharp decrease in unemployment can increase the level of inflation beyond the expected level” 38.

6.4. The problem of determining the strength of influence of factors

So, the most important problem of cognitive modeling is identifying the weights of graph arcs - that is, quantitative assessment of the mutual influence or influence of factors. The fact is that the cognitive approach is used when studying an unstable, weakly structured environment. Let us recall that its characteristics are: variability, difficulty in formalizing, multi-factorial nature, etc. This is the specificity of all systems in which people are included. Therefore, the inoperability of traditional mathematical models in many cases is not a methodological defect of cognitive analysis, but a fundamental property of the subject of research 39 .

Thus, the most important feature of most situations studied in management theory is the presence of thinking participants in them, each of whom represents the situation in their own way and makes certain decisions based on “their” perception. As J. Soros noted in his book “The Alchemy of Finance,” “When there are thinking participants in a situation, the sequence of events does not lead directly from one set of factors to another; instead, it cross-cuts...connects factors to their perceptions and perceptions to factors.” This leads to the fact that “the processes in the situation do not lead to equilibrium, but to a never-ending process of change” 40. It follows that a reliable prediction of the behavior of processes in a situation is impossible without taking into account the assessment of this situation by its participants and their own assumptions about possible actions. J. Soros called this feature of some systems reflexivity.
Formalized quantitative dependencies of factors are described by different formulas (patterns), depending on the subject of the study, that is, on the factors themselves. However, as already mentioned, building a traditional mathematical model is not always possible.

The problem of universal formalization of the mutual influence of factors has not yet been solved and is unlikely to ever be solved.

Therefore, it is necessary to come to terms with the fact that it is not always possible to describe the relationships of factors with mathematical formulas, i.e. It is not always possible to accurately quantify the dependencies 41 .
Therefore, in cognitive modeling, when estimating the weights of arcs, as mentioned, the subjective opinion of the expert is often taken into account 42. The main task in this case is to compensate for subjectivity and distortion of assessments through various types of verification procedures.

In this case, checking the expert’s assessments for consistency is usually not enough. The main goal of the procedure for processing the subjective opinions of an expert is to help him reflect, more clearly understand and systematize his knowledge, evaluate its consistency and adequacy to reality.

In the process of extracting expert knowledge, there is an interaction between the expert - the source of knowledge - and a cognitive scientist (knowledge engineer) or with a computer program, which makes it possible to follow the progress of the specialists' reasoning when making decisions and to identify the structure of their ideas about the subject of research 43 .
The procedures for testing and formalizing an expert’s knowledge are described in more detail in the article by A.A. Kulinich “Cognitive modeling system “Canva”” 44.

7. Checking the adequacy of the model
Researchers have proposed several formal procedures for checking the adequacy of the constructed model 45 . However, since the model is not built only on formalized relationships between factors, mathematical methods for checking its correctness do not always provide an accurate picture. Therefore, the researchers proposed a kind of “historical method” to test the adequacy of the model. In other words, the developed model of a situation is applied to similar situations that existed in the past and the dynamics of which are well known 46 . If the model turns out to be operational (that is, it produces forecasts that coincide with the actual course of events), it is recognized as correct. Of course, no single method of model verification is exhaustive, so it is advisable to use a set of procedures for verifying correctness.

8. Using a cognitive model

8.1. Application of cognitive models in decision support systems
The main purpose of the cognitive model is to help the expert in the process of cognition and, accordingly, develop the right decision. Therefore, the cognitive approach is used in decision support systems.
The cognitive model visualizes and organizes information about the environment, intent, goals, and actions. At the same time, visualization performs an important cognitive function, illustrating not only the results of the actions of the subject of management, but also suggesting to him ways to analyze and generate decision options 47 .
However, the cognitive model serves not only to systematize and “clarify” the expert’s knowledge, but also to identify the most advantageous “points of application” of the control actions of the subject of management 48 . In other words, the cognitive model explains which factor or relationship of factors needs to be influenced, with what force and in what direction in order to obtain the desired change in target factors, that is, to achieve the management goal at the lowest cost.
Control actions can be short-term (impulse) or long-term (continuous), acting until the goal is achieved. It is also possible to use pulsed and continuous control actions together 49 .
When a given goal is achieved, the task immediately arises of maintaining the situation in the achieved favorable state until a new goal appears. In principle, the task of maintaining the situation in the required state is no different from the task of achieving a goal 50.
A complex of interrelated control influences and their logical time sequence constitute a holistic management strategy (control model).
The use of different management models can lead to different results. Here it is important to be able to predict what consequences this or that management strategy will ultimately lead to.
To develop such forecasts, a scenario approach (scenario modeling) is used within the framework of cognitive analysis. Scenario modeling is sometimes called "dynamic simulation".
The scenario approach is a kind of “playing out” different options for the development of events depending on the chosen management model and the behavior of unpredictable factors. For each scenario, a triad is built: “initial premises - our impact on the situation - the result obtained” 51. In this case, the cognitive model makes it possible to take into account the entire complex of effects of control actions for different factors, the dynamics of factors and their relationships under different conditions.
Thus, all possible options for the development of the system are identified and proposals are developed regarding the optimal management strategy for implementing the desired scenario from among the possible ones 52 .
Researchers quite often include scenario modeling among the stages of cognitive analysis or consider scenario modeling as an addition to cognitive analysis.
If we summarize and generalize the opinions of researchers regarding the stages of scenario modeling, then in the most general form the stages of scenario analysis can be presented as follows.
1. Development of management goals (desired changes in target factors).
2. Development of scenarios for the development of the situation when applying different management strategies.
3. Determining the achievability of the goal (the feasibility of scenarios leading to it); checking the optimality of the already planned management strategy (if any); choosing the optimal strategy that corresponds to the best scenario from the point of view of the goal.
4. Concretization of the optimal management model - development of specific practical recommendations for managers. This specification includes identifying control factors (through which it is possible to influence the development of events), determining the strength and direction of control influences on control factors, predicting probable crisis situations due to the influence of unpredictable external factors, etc.
It should be noted that the stages of scenario modeling may vary depending on the object of study and management.
At the initial stage of modeling, there may be enough qualitative information that does not have an exact numerical value and reflects the essence of the situation. When moving to modeling specific scenarios, the use of quantitative information, which represents numerical estimates of the values of any indicators, becomes increasingly important. In the future, mainly quantitative information 53 is used to carry out the necessary calculations.
The very first scenario, which does not require any action by the researcher to form it, is the self-development of the situation (in this case, the vector of control actions is “empty”). Self-development of the situation is the starting point for further formation of scenarios. If the researcher is satisfied with the results obtained during self-development (in other words, if the set goals are achieved during self-development), then further scenario research comes down to studying the impact of certain changes in the external environment on the situation 54 .
There are two main classes of scenarios: scenarios that simulate external influences and scenarios that simulate the targeted (controlled) development of the situation 55 .

8.2. An example of working with a cognitive model

Let's consider an example of working with a cognitive model given in the article by S.V. Kachaeva and D.I. Makarenko “Integrated information and analytical complex for situational analysis of the socio-economic development of the region.”
“The use of an integrated information and analytical complex of situational analysis can be considered using the example of developing a strategy and program for the socio-economic development of the region.
At the first stage, a cognitive model of the socio-economic situation in the region is built... Next, scenarios of the potential and real possibility of changing the situation in the region and achieving the set goals are modeled.
The following were chosen as the goals of socio-economic policy:

To achieve the set goals, the following “levers” were selected (controlling factors - Yu.M.), with the help of which the decision maker can or wants to influence the situation:

As a result of the simulation, the potential and real possibility of achieving the set goals with the help of the selected levers and the resulting control influences is clarified (see Fig. 3).

Figure 3. Cognitive and dynamic simulation (scenario) modeling.

At the next stage, they move from developing a strategy for achieving goals to developing a program of specific actions. The tool for implementing the strategy is regional budget and tax policy.
The levers and certain impacts selected at the previous stage correspond to the following directions of budget and tax policy.

Levers of achievement strategic goals	Directions of budget and tax policy
Income of the population	Expenditures on social policy
Investment climate	Government expenses Law enforcement expenses Expenses for industry, power generation, construction and agriculture
Production costs	Regulation of tariffs for electricity, fuel, heat, rent, etc.
Development of production infrastructure	Development of market infrastructure
Tax collection	Regulating the level of tax non-payments
Tax benefits	Regulating the level of tax benefits
Political and economic preferences for the region.	Free transfers from other levels of government

Thus, an integrated information and analytical complex of situational analysis is a powerful tool for developing a regional development strategy and implementing this strategy” 56 .
It should be noted that in studies, examples of the use of cognitive and scenario modeling are usually given in a very general form, since, firstly, this kind of information is exclusive and has a certain commercial value, and, secondly, each specific situation (system, environment, control object) requires an individual approach.
The existing theoretical basis of cognitive analysis, although it requires clarification and development, allows different management subjects to develop their own cognitive models, since, as mentioned, it is assumed that specific models are compiled for each area, for each problem.

9. Computer systems to support management decisions

Conducting cognitive analysis of unstable, weakly structured situations and environments is an extremely difficult task, for the solution of which information systems are involved. Essentially, these systems are designed to improve the efficiency of the decision-making mechanism, since the main applied task of cognitive analysis is control optimization.

9.1. General characteristics of decision support systems
Decision support systems are usually interactive. They are designed to process data and implement models that help solve individual, mostly weakly or unstructured problems (for example, making investment decisions, making forecasts, etc.). These systems can provide workers with the information needed to make individual and group decisions. Such systems provide immediate access to information reflecting current situations and all the factors and connections necessary for decision making 57
etc.................

Figure 3. Cognitive map for analyzing the problem of electricity consumption in the region

Arc () has a “+” sign, since environmental improvement leads to an increase in the number of inhabitants, and environmental deterioration causes an outflow of population. Arc () has a “-” sign, since an increase in energy consumption worsens the state of the environment, and a decrease in energy consumption has a beneficial effect on its condition. Arc () has a “+” sign due to the fact that an increase in the number of inhabitants causes an increase in energy consumption and, conversely, a decrease in population leads to a decrease in energy consumption.

Let's consider the interaction of factors in the circuit. Let's assume that the population has increased. This will lead to increased energy consumption and therefore deteriorate the environment, which in turn will lead to a decrease in the number of inhabitants. Thus, the influence of the impulse at the vertex will be compensated by the action of the contour, and the behavior of the system will stabilize. Three factors form a circuit that counteracts deviation.

In the contour, all the arcs have a “+” sign, and it is easy to see that an increase (decrease) in any variable in this contour will be amplified. As mentioned above, in mathematical language a cognitive map is called a signed directed graph. A contour in a graph is understood as a closed oriented path, all of whose vertices are different.

The contours in a cognitive map correspond to feedback loops. The circuit that enhances the deviation is a positive feedback loop, and the circuit that counteracts the deviation is a negative feedback loop. The Japanese scientist M. Maruyama called these circuits morphogenetic and homeostatic, respectively. In the same work, Maruyama proved that a contour enhances deflection if and only if it contains an even number of negative arcs or does not contain them at all, otherwise it is a contour that counteracts deflection. Indeed, in the case of an even number of negative arcs, opposition to the deviation will itself be counteracted. If the number of negative arcs is odd, then the last opposition to the deflection is unopposed.

This analysis scheme largely corresponds to intuitive ideas about causality. It is clear that the interaction of two factors may be subject to more complex patterns, but in this case, languages of functional relationships should be used to describe the process under study.

Experience in using cognitive maps shows that the researcher often over-simplifies the situation due to limited cognitive capabilities, difficulties in simultaneously taking into account a large number of factors, and their dynamic interaction. M. Wertheimer wrote that the researcher often lacks breadth of vision in complex situations that include several subproblems, understanding of the whole is lost, and a narrow view of the problem is self-imposed.

D. Hayes's monograph on causal analysis emphasizes that few interesting phenomena in the social sciences depend on only one cause. Social phenomena usually include many different events and trends determined by several factors, each in turn influencing a number of other factors. Networks of causal relationships are formed, i.e. Causality is systemic in nature. Causality generates a model of social phenomena, and the study of models provides a deeper understanding of the causal relationships that gave rise to them.

By analyzing his own and others’ cognitive maps, a researcher can quickly deepen his understanding of a problem and improve the quality and validity of decisions made. In addition, a cognitive map is a convenient tool for changing established stereotypes and contributes to the generation of new points of view. Thus, in the work of M. Maruyama, an example is given of the erroneous belief (cognitive cliché) that trade between two countries is a zero-sum game. If one partner wins, the other loses just as much. This belief is the psychological background of the war of restrictions on the import of goods (imports).

For a country that has a trade deficit with another country, at first glance there are two equivalent ways to improve the trade balance: reduce imports and increase exports. However, the war of restrictions leads to a negative overall effect: due to a reduction in the turnover of capital between the two states and an increase in unemployment, both sides lose. On the contrary, mutual export expansion increases the speed of capital circulation and has a positive effect for both countries.

A cognitive map is especially useful for analyzing the effects of factors that are difficult to formalize, the measurement of which is often a very difficult problem.

The English scientist K. Eden proposed using cognitive maps for collective decision-making and decision-making. K. Eden emphasizes the importance of the fact that the effectiveness of interaction in a group of decision-makers depends significantly on the extent to which each participant understands the ways in which situations are interpreted by other group members. An important role in obtaining consensus is played by the achievement by group members of unity in the way of constructing future events, the processes of “strengthening understanding”, “changing symbols”, identifying new points of view. A tool is needed to record and analyze opinions, which are often based on the experience and intuition of experts. It is important to be able to record the contradictory points of view of experts without losing the richness of the argumentation. A cognitive map makes it possible to trace the relationships between the future, present and past of the process being studied.

It is clear that using cognitive maps for planning in an organization may require recording several thousand interrelated statements. Therefore, to record, store, search and analyze information, it is necessary to use a computer and special software. Currently, a number of commercial packages have been developed for the analysis of cognitive maps (NIPPER, Cope, GISMO).

The computer can be used for the following purposes:

§ searching for concepts containing a specific set of keywords;

§ searching for clusters in the map, i.e. groups of interrelated concepts that are close to each other;

§ finding map outputs (statements without consequences);

§ searching for statements that are central to a large number of arguments;

§ determination of statements with the greatest argumentation;

analysis of connections between expressed opinions and the structure of the organization.

The cognitive map represents the “synthetic wisdom” of the organization’s team and accumulates the views of people, many of whom have never met. Each participant in the process must be sure that his opinion is taken into account and can influence the organization's strategy. Therefore, it is desirable that the organization's employees are included in this process on a regular basis, and they should know that other employees are also included in the strategy formation process. With the help of various working groups and committees, individual parts of the strategic plan are refined and, most importantly, feedback effects are monitored.

This approach allows you to get rid of a number of circumstances that prevent effective decisions from being made: a narrowing view of reality under the influence of habitual experience, boredom and the ritual nature of planning, ossification of organizational structures, the influence of stereotypes, ambitions, etc.

The cognitive modeling technique, as a rule, involves a certain sequence of actions. It involves dividing the environment relevant to the problem under study into external and internal. The external environment is something that practically and obviously does not depend on the person (manager, subject, leader, leader, organization, etc.) interested in solving the problem that has arisen, but influences the solution of this problem, and the internal environment is what this person may change.

Then the factors (notions, concepts) characterizing the situation are identified and the mutual influences between them are assessed. Sometimes factors are immediately divided into positive (positive) and negative (negative) factors. At first, there may be too many such factors to help solve the problem (about 100-120), so special “compression” procedures are used to reduce them to 5-25.

At the next stage, it is necessary to involve expert assessments to fill the resulting diagram with specific meanings, which makes it possible to answer the question of what factors a person can influence directly, as well as factors whose values would like to be changed, but it is impossible to do so directly.

Based on expert assessments and their corresponding analysis, possible scenarios for the development of the situation and options for actions taken are selected, on the basis of which the modeling of the situation in its dynamics is implemented. The result of cognitive modeling should be the formulation of the most suitable action strategy for a person, taking into account not only external benefits and limitations, but also the requirements of the internal environment.

Cognitive modeling is, first of all, quickly obtaining answers to questions like “What will happen if ...?” and “What needs to be done to...?” through identifying factors and their mutual influences in the emerging weakly determined and unstable situation, where the dynamics of the problem solving process are greatly influenced by people, and the formulation of the problem is most often inverse and incorrect.

Trends in the development of cognitive modeling methods are formed in the context of improving methods of situational analysis, as well as other theoretical and applied analytical research, namely:

· from informing participants - to extracting knowledge and understanding;

· from reference work - to analytical;

· from one participant - to groups;

· from analysis of the internal environment - to the external one;

· from extrapolation of trends - to the search for extraordinary goals and paths;

· from data recording to knowledge management;

· from information security - to sustainable management;

· from accuracy - to intelligence;

Cognitive modeling is a unique and practical way to support strategic and tactical management, ensuring increased confidence in the leader; increasing confidence in the correctness of actions; achieving management satisfaction with the quality of meetings; prompt search for good measures and solutions; preventing conflicts and crises; deep understanding of problems; convenient and visual resource management.

The technology of cognitive analysis and modeling (Fig. 4) is based on the cognitive (cognitive-target) structuring of knowledge about an object and its external environment.

Individual work

Cognitive modeling

Introduction

1. Concepts and essence of “Cognitive modeling” and “Cognitive map”

2. Problems of the cognitive approach

Conclusion

List of used literature

INTRODUCTION

Cognitive analysis and modeling are fundamentally new elements in the structure of decision support systems.

1. Concepts and essence of “Cognitive modeling” and “Cognitive map”

A cognitive map (from Latin cognitio - knowledge, cognition) is an image of a familiar spatial environment.

The technology of cognitive analysis and modeling (Figure 1) is based on the cognitive (cognitive-target) structuring of knowledge about an object and its external environment.

Figure 1. Technology of cognitive analysis and modeling

The results of cognitive structuring are displayed using a cognitive map (model).

2. Cognitive (cognitive-target) structuring of knowledge about the object under study and its external environment based on PEST analysis and SWOT analysis

The selection of basic factors is carried out by applying PEST analysis, which identifies four main groups of factors (aspects) that determine the behavior of the object under study (Figure 2):

P olicy - politics;

E economy - economy;

S ociety - society (sociocultural aspect);

T echnology - technology

Figure 2. PEST analysis factors

For each specific complex object there is its own special set of the most significant factors that determine its behavior and development.

These changes may pose a threat to the development of the object, or, conversely, provide new opportunities for its successful development.

The next step is a situational analysis of problems, SWOT analysis (Figure 3):

S trengths - strengths;

W eaknesses - shortcomings, weaknesses;

O pportunities - opportunities;

T hreats - threats.

Figure 3. SWOT analysis factors

Opportunities are defined as circumstances conducive to the favorable development of an object.

Threats are situations in which damage to an object may be caused, for example, its functioning may be disrupted or it may lose its existing advantages.

Based on the analysis of various possible combinations of strengths and weaknesses with threats and opportunities, the problem field of the object under study is formed.

The problem field is a set of problems that exist in the modeled object and the environment, in their relationship with each other.

The availability of such information is the basis for determining development goals (directions) and ways to achieve them, and developing a development strategy.

The stages of cognitive technology and their results are presented in Table 1:

Table 1

Stages of cognitive technology and results of its application

Stage name	Result presentation form
1. Cognitive (cognitive-target) structuring of knowledge about the object under study and its external environment based on PEST analysis and SWOT analysis: Analysis of the initial situation around the object under study, highlighting the basic factors characterizing economic, political and other processes occurring in the object and in its macroenvironment and influencing the development of the object. 1.1 Identification of factors characterizing the strengths and weaknesses of the object under study 1.2 Identification of factors characterizing opportunities and threats from the external environment of the object 1.3 Construction of the problem field of the object under study	Report on a systemic conceptual study of an object and its problem area
2. Construction of a cognitive model of object development - formalization of knowledge obtained at the stage of cognitive structuring 2.1 Identification and justification of factors 2.2 Establishment and justification of relationships between factors 2.3 Construction of a graph model	Computer cognitive model of an object in the form of a directed graph (and matrix of factor relationships)
3. Scenario study of trends in the development of the situation around the object under study (with the support of the software systems "SITUATION", "COMPASS", "KIT") 3.1 Determining the purpose of the study 3.2 Setting research scenarios and modeling them 3.3 Identification of development trends of an object in its macroenvironment 3.4 Interpretation of scenario study results	Report on the scenario study of the situation, with interpretation and conclusions
4. Development of strategies for managing the situation around the object under study 4.1 Definition and justification of the management goal 4.2 Solving the inverse problem 4.3 Selection of management strategies and ordering them according to criteria: possibility of achieving the goal; risk of losing control of the situation; emergency risk	Report on the development of management strategies with justification of strategies according to various criteria of management quality
5. Search and justification of strategies for achieving goals in stable or changing situations For stable situations: a) selection and justification of the management goal; b) selection of activities (controls) to achieve the goal; c) analysis of the fundamental possibility of achieving the goal from the current state of the situation using selected activities; d) analysis of real restrictions on the implementation of selected activities; e) analysis and justification of the real possibility of achieving the goal; f) development and comparison of strategies for achieving the goal by: proximity of management results to the intended goal; costs (financial, physical, etc.); by the nature of the consequences (reversible, irreversible) from the implementation of these strategies in a real situation; on the risk of emergency situations For changing situations: a) selection and justification of the current management goal; b) in relation to the current goal, the previous paragraphs b-f are valid; c) analysis of changes occurring in the situation and their display in a graph model of the situation. Go to point a.	Report on the development of strategies for achieving goals in stable or changing situations
6. Development of a program for implementing the development strategy of the object under study based on dynamic simulation modeling (with the support of the Ithink software package) 6.1. Distribution of resources by area and over time 6.2 Coordination 6.3 Monitoring of execution	Program for implementing the site development strategy. Computer simulation model of object development