COGNITIVE MODELING AS A TOOL IN THE PROCESS OF KNOWLEDGE LARGE SYSTEMS Galina Gorelova CML-2010, Dubrovnik Cognitive Mechanisms for Decision Making Cognitive.

COGNITIVE MODELING AS COGNITIVE MODELING AS A TOOL IN THE PROCESS A TOOL IN THE PROCESS OF KNOWLEDGE LARGE OF KNOWLEDGE LARGE

SYSTEMSSYSTEMS

Galina Galina GorelovaGorelova

CML-2010, DubrovnikCML-2010, Dubrovnik

Cognitive Mechanisms for Decision Making Cognitive Aspects of Information Technologies Development and

Using

22

Technological Instituteat South Federal University, Taganrog

33

ContentsContents::

1.Introduction1.Introduction:: The problem of understanding the The problem of understanding the process of learning a Large-scale systemsprocess of learning a Large-scale systems.. SSustainable ustainable

developmentdevelopment Large-scale systemsLarge-scale systems 2. Basic concepts associated with 2. Basic concepts associated with

cognitive modelingcognitive modeling3. Formalizing the problem of the study 3. Formalizing the problem of the study

of a larger systemof a larger system4. Presentation of the main tasks, 4. Presentation of the main tasks,

models and methods in cognitive models and methods in cognitive modeling technologymodeling technology

5. 5. The scheme of interrelated The scheme of interrelated techniques of cognitive methodologytechniques of cognitive methodology

6.6.Examples of cognitive modelingExamples of cognitive modeling


44

Introduction.Introduction. The problem of understanding the process of The problem of understanding the process of

learning learning a Large-scale systemsa Large-scale systems..

Sustainable developmentSustainable development Large-scale systemsLarge-scale systems


Using


55

The problem of understanding the process of The problem of understanding the process of learning a Large-scale systems. Is it possible to learning a Large-scale systems. Is it possible to

"manage" this process?"manage" this process?

The purpose of the study of a Large-scale The purpose of the study of a Large-scale systemssystems? ?

Can sustainable development of a Large-scale Can sustainable development of a Large-scale systems?systems?

How does the expert having the idea of How does the expert having the idea of applying knowledge from one area to study applying knowledge from one area to study specific complex system? How, in what specific complex system? How, in what sequence and why this knowledge is applied? sequence and why this knowledge is applied? How does it directs the process of learning? How does it directs the process of learning? What were the results may lead the What were the results may lead the management of a complex system of management of a complex system of knowledge?knowledge?

One theory, a method (or even a group One theory, a method (or even a group of methods) do not allow to consider all of methods) do not allow to consider all aspects of the problems of a large aspects of the problems of a large system. Most consider only the side system. Most consider only the side effects, which directed the attention of effects, which directed the attention of the researcher or determined by the the researcher or determined by the social ordersocial order

The methodology of cognitive modeling is developed as a product of synthesis and utilization of systems theory and systems analysis, operations research,, management theory, decision theory, statistics, mathematical programming, intelligent systems, etc.

66

The main objectives: Study and understanding of the mechanism of phenomena in Large-scale systems, prediction of their possible development paths for the development of governance aimed at sustainable development and the prevention

Object of research : Large-scale Systems (socio-economic, environmental, social engineering, etc.) Subject of research: The phenomena and processes in Large-scale systems, models and methods for the study of Large-scale

systems


Using


77

Researching of the problem of Researching of the problem of ««sustainable sustainable developmentdevelopment»» of complicated socio-economic, of complicated socio-economic, political and ecological systems in its complex political and ecological systems in its complex comprehension as interdisciplinary problem and multi-comprehension as interdisciplinary problem and multi-aspect strategy has been determined among the main aspect strategy has been determined among the main tasks in the international community in the mid-90s of tasks in the international community in the mid-90s of the last century.the last century.

A complex problem and possible approaches of its A complex problem and possible approaches of its solution for Russia is presented in the encyclopedic solution for Russia is presented in the encyclopedic monograph Koptyug et al.monograph Koptyug et al.

New paradigm jf Russia's development in the XXI centuryNew paradigm jf Russia's development in the XXI century

(Comprehensive analysis of the problems of sustainable development: ideas and results)/ Ed. (Comprehensive analysis of the problems of sustainable development: ideas and results)/ Ed. V.A. Koptyug, V.M. Matrosov, V.K. LevashovV.A. Koptyug, V.M. Matrosov, V.K. Levashov. M.: "Academia", 2000, 416 . M.: "Academia", 2000, 416 pppp..

The most close to the notion of «sustainable The most close to the notion of «sustainable development» term in Russia understanding is the development» term in Russia understanding is the concept of «concept of «noospheric developmentnoospheric development» [Vernadcky]. » [Vernadcky].

Sustainable developmentSustainable development


Using


88

The notion of «The notion of «Sustainable Sustainable developmentdevelopment»»We assume the followingWe assume the following [New paradigm…][New paradigm…] : :

««Sustainable developmentSustainable development of a system is a complex dynamic of a system is a complex dynamic feature of class manageability, combining the requirementsfeature of class manageability, combining the requirements : :

1) 1) hit of development trajectory at a certain time in the target set hit of development trajectory at a certain time in the target set of states;of states;

2) no trajectory spillover in the prospective time range of a certain 2) no trajectory spillover in the prospective time range of a certain

number of "safe" states;number of "safe" states;

3) almost monotone increasing of some indicators of development 3) almost monotone increasing of some indicators of development (for example, quality of life, etc.) at a certain time interval and (for example, quality of life, etc.) at a certain time interval and then saving them in the specified range of admissible values; then saving them in the specified range of admissible values;

4) an asymptotic stability (stabilize ability) of program trajectory; 4) an asymptotic stability (stabilize ability) of program trajectory;

5) 5) harmonizing interests of sidesharmonizing interests of sides».».


99

where where L, F, J, S, B, Z, RL, F, J, S, B, Z, R - - performance evaluation of global performance evaluation of global security for safety of world development in the model (1);security for safety of world development in the model (1); LL - - life expectancy; life expectancy; F F - consumption per capita food (food per - consumption per capita food (food per person); person); J J - consumption of industrial goods per capita - consumption of industrial goods per capita (industrial goods per person); (industrial goods per person); SS - average social spending per - average social spending per capita (services per person); capita (services per person); B B - biomass of terrestrial - biomass of terrestrial vegetation; vegetation; ZZ - the level of pollution; - the level of pollution; RR - remaining at the end - remaining at the end of the XXI century natural resources (volume traditional, non-of the XXI century natural resources (volume traditional, non-renewable, and non-traditional, reclaimed, natural resources). renewable, and non-traditional, reclaimed, natural resources). Maximum value of Maximum value of LL, , FF, , JJ, , SS, , BB, , ZZ, , RR are selected on the basis are selected on the basis of medical, sociological and environmental research in of medical, sociological and environmental research in international projects or on the basis of estimates given in the international projects or on the basis of estimates given in the decisions of international forums and organizations decisions of international forums and organizations

Global security - is "vital security interests of the world's Global security - is "vital security interests of the world's population (current and future generations and nature (the population (current and future generations and nature (the Earth's biosphere)) from threats to their survival and Earth's biosphere)) from threats to their survival and sustainable development (of global disasters), taking into sustainable development (of global disasters), taking into account the factors of the global economy"account the factors of the global economy" [The New Paradigm ..., c. 13]:[The New Paradigm ..., c. 13]:

(1) L(t)>L; F(t)>F; J(t)>J; S(t)>S; B(t)>B; Z(t)>Z; R(t)>R

t[t0; t1],


1010

2. Basic concepts2. Basic concepts associated with associated with

cognitive modelingcognitive modeling


Using


The content and program of research of complex systems can be specified as a model of a meta-system research

11


1. Сложность структуры

1.1. Большое количество элементов и связей (многослойная, иерархическая и т.п.);1.2. Большое количество взаимодействий между элементами и окружающей средой (часто слабые взаимодействия повышают сложность системы)

Степень информированности лица, принимающего решение

5.Проблемы принятия решений:

5.1.структурированные,5.2. слабоструктурированные 5.3. неструктурированные

2.Сложность поведения

внутреннего, внешнего(иногда непредсказуемость поведения),динамика системы

4.Закономерности систем:

4.1.взаимодействия частей и целого (целостность, интегративность);4.2. иерархической упорядоченности систем (коммуникативность, иерархичность - эта группа закономерностей тесно связана с закономерностью целостности, с расчленением целого на части, взаимодействием системы с окружающей средой, т.е. надсистемой, и подчиненными системами;4.3. функционирования и развития систем (историчность, самоорганизация);4.4. осуществимости систем (эквифинальность, закон необходимого разнообразия, потенциальная эффективность).

3. Вычислительная сложность

6.Информационная ситуация:

6.1. принципиальная неопределенность (квантовая механика); 6.2. неопределенность, генерированная общим большим числом объектов, включенных в ситуацию (например, 109); 6.3. неопределенность, вызванная недостатком информации и ее достоверности в силу технических, социальных и иных причин; 6.4. неопределенность, порожденная слишком высокой платой за определенность; 6.5. неопределенность, порождаемая ЛПР в силу недостатка его опыта и знаний факторов, влияющих на принятие решений; 6.6. неопределенность, связанная с ограничениями в ситуации принятия решений (время, финансы и др.); 6.7. неопределенность, вызванная поведением среды или противника, влияющего на процесс принятия решений

Характерные признаки большой системы и ее сложности

В процессе познания системы происходит «раскрытие неопределенности» - когнитивная структуризации

знаний эксперта

1. Система открытая, взаимодействует с внешней средой2. В системе есть активные элементы

1212

3. Formalizing the problem 3. Formalizing the problem of the study of the study

of a larger systemof a larger system


The content and program of research of complex systems can be specified as a model of a meta-system research


Using

1313

All of this is incorporated in a formal meta-studies and decision-All of this is incorporated in a formal meta-studies and decision-making. making. Original model - the model proposed in the works Original model - the model proposed in the works Kulba V.VKulba V.V.. (ISP RAS)(ISP RAS)::

The main feature of our research - The main feature of our research - cognitive integrationcognitive integration in in the system of both known and newly developed methods the system of both known and newly developed methods

and modelsand models

MO (Y, U, P) - identifies a model system i which the vector Y - endogenous variables, characterizing the phase state of the object, U - vector of controlled variables, P - vector of resources allocated; ME (X) - a model of the environment, X - exogenous variables;

MOE - model of interaction between the object and the environment;MD (Q) - a model of system behavior, Q - the perturbing effects;MMO and MME - model for measuring the state of the system and the

environment; MU - model management systems (not included in the meta, if only to

solve the problem the study site); Mн - a model of expert; A - generally the choice processes of change of the object

ССognitive ognitive integrationintegration

{ ( , , ), ( ), , ( ), , , , , }o E OE D MO ME UM M Y U P M X M M Q M M M Ì í A{ ( , , ), ( ), , ( ), , , , , }o E OE D MO ME UM M Y U P M X M M Q M M M Ì í A


Using


14

MO (Y, U, P)

ME (X)

MOE

Mн

{ ( , , ), ( ), , ( ), , , , , }o E OE D MO ME UM M Y U P M X M M Q M M M Ì í A


1515

The main distinguishing feature of our researchThe main distinguishing feature of our research - - cognitive integrationcognitive integration in the system of both known in the system of both known and newly developed methods and models created in and newly developed methods and models created in the process of cognition of the object entity.the process of cognition of the object entity.

The ideal goalThe ideal goal - creating a tool which implements a - creating a tool which implements a union and to help you develop and validate a strategy union and to help you develop and validate a strategy for sustainable development of for sustainable development of Large-scale Systems

ImportantImportant!! Addressing the challenges of sustainable Addressing the challenges of sustainable development of complex systems requires an interdisciplinary development of complex systems requires an interdisciplinary approach!approach!

In our studies, this campaign is implemented by In our studies, this campaign is implemented by means of cognitive modeling, means of cognitive modeling, cognitive cognitive

integrationintegration of disparate knowledge in various of disparate knowledge in various fields of knowledgefields of knowledge..

Cognitive integrationCognitive integration


Using


1616

Cognitive integrationCognitive integration - a process - a process that takes place in the minds of that takes place in the minds of the expertthe expert..And - this is important!And - this is important! carried out by a continuous, iterative process of carried out by a continuous, iterative process of

decision-making expert, supported by special tools. decision-making expert, supported by special tools. We are now on the way to develop the appropriate We are now on the way to develop the appropriate supporting mathematical and software tools for this. supporting mathematical and software tools for this. And try to understand and explain why and how And try to understand and explain why and how such integration occurs. And how it can be such integration occurs. And how it can be practically usedpractically used. .

Apparently, the latter is an area of contact research in the field of Apparently, the latter is an area of contact research in the field of cognitive psychology, linguistics, neurophysiology, intelligent cognitive psychology, linguistics, neurophysiology, intelligent systems, artificial intelligence and so on. systems, artificial intelligence and so on.

Thus, Thus, the process of cognition of the object entity the process of cognition of the object entity and its results are included deliberately by us in the and its results are included deliberately by us in the process of process of cognitive modelingcognitive modeling

Currently, under the Currently, under the cognitive modelingcognitive modeling, we understand the , we understand the interlinked problems of systeminterlinked problems of system


Using


1717

4. Presentation of the 4. Presentation of the main tasks, models and main tasks, models and

methods in cognitive methods in cognitive modeling technologymodeling technology


Using


1818

22. . System tasks of cognitive System tasks of cognitive analysisanalysis

1.1. Identification of Identification of the objectthe object

2. Analysis of the 2. Analysis of the ways and cyclesways and cycles

3. Scenario analysis3. Scenario analysis4. Solve the inverse 4. Solve the inverse

problemproblem

5. Analysis of sustainability5. Analysis of sustainability 6.6. ObservabilityObservability7. Controllability7. Controllability8. Connectedness, 8. Connectedness, complexitycomplexity9. Optimization9. Optimization10. Adaptability10. Adaptability11. Self-organization11. Self-organization12. Disasters12. Disasters13. Sensitivity studies13. Sensitivity studies14. Search for solutions 14. Search for solutions gamesgames15. Decision-making15. Decision-making

««NewNew»» task taskof cognitive of cognitive analysisanalysis

««TraditionalTraditional»» task task of cognitive of cognitive analysisanalysis

Cognitive Mechanisms for Decision Making

Cognitive Aspects of Information Technologies Development and Using


1919

1. 1. Identification Identification of the objectof the object

ScenarioScenario №1 (q1=+1) ScenarioScenario №2 (q1=+1, q3= - 1)

3. Scenario analysis3. Scenario analysis

EXAMPLEEXAMPLE

00010

10010

11000

00100

11110

5

4

3

2

1

4321 5

V

V

V

V

V

VVVVV

RG

Figure Figure 1.1.

Figures Figures 2.2.


2020

33. . Cognitive Cognitive modelsmodels

GG is a cognitive map, and i=1,2,…n is a set of vertices is a cognitive map, and i=1,2,…n is a set of vertices (objects of the studied system, for example, (objects of the studied system, for example, production, population, resources, etc.); is a set of production, population, resources, etc.); is a set of edges - relationship between objects in the system edges - relationship between objects in the system (positive, negative, zero in observing situation), g = (positive, negative, zero in observing situation), g = 1,2, ... k, 1,2, ... k,

F = F (X, E) = F (xF = F (X, E) = F (xii, x, xjj,, eeijij) is edge transformation functional ) is edge transformation functional that relates to each edge a sign, or a weight coefficient that relates to each edge a sign, or a weight coefficient wwijij, or a function F(x, or a function F(xii , x , xjj , e , eijij) = f) = fijij

,G V E

,,, FXGФ

Cognitive mapCognitive map::

Parametric vector of function graphParametric vector of function graph::

((3)3)

(4)(4)

3.1. Known cognitive models3.1. Known cognitive models

wherewhere::

The taskThe task: : 1. Identification of the object1. Identification of the object


Using


2121

3.2. Hierarchical cognitive models3.2. Hierarchical cognitive modelsV(0)

Vi(k

)

Vi(1)

IG = <Gk, Gk+1,Ek,>, k ≥ 2,

wherewhere::

GGkk=<{=<{vvii((kk))},}, { {ееijij((kk)) }>, }>,

wherewhere:: GGkk - - is a cognitive mapis a cognitive map

kk--level,level,

VV(1)(1) ={={vvii(1)(1) }} – – set of vertices set of vertices

of the lower levelof the lower level,,

VV((kk)) ={={vvii((kk))}} – – the set of the set of

vertices vertices kk level, level,Relationship between the vertices Relationship between the vertices

of one level- the arcof one level- the arc ееijij((kk)),, ЕЕ((kk)) = { = {ееijij((kk))}; }; relations relations

between vertices of differentbetween vertices of different

levellevel– – ее kk,,kk+1+1, , EEkk = { = {ееkk,,kk+1+1}.}.

(5)(5)

Figure 3.Figure 3.


Using


22

( 1) ( 1), , , , , , , ,AB Ak A k Ak Bk B k Bk A BIGG G G E G G E R IG IG R

V(0)

V(k)

V(1)

V(0)

V(k)

V(1)

, , , , ,Pr , ,Г iГ I A F U R n

Interaction systems:

3.3. 3.3. Simulation games on hierarchical Simulation games on hierarchical cognitive maps in the interaction of complex cognitive maps in the interaction of complex systemssystems

Model of multistep games

Figure 4.Figure 4.Cognitive Mechanisms for Decision Making Cognitive Aspects of Information Technologies Development and

Using


2323

where where ххii(n) - the value of impulse at the vertex (n) - the value of impulse at the vertex vvii in the in the previous moment - cycle modeling (n), previous moment - cycle modeling (n), ххii(n+1) - a (n+1) - a researcher interested in the (n +1) moment; fresearcher interested in the (n +1) moment; fijij – impulse – impulse conversion function; Pconversion function; Pjj(n)- the value momentum at the (n)- the value momentum at the vertices vertices vvjj, adjacent to the vertex , adjacent to the vertex vvii; ; QQii(n) - vector of (n) - vector of disturbances and control actions made to the top of disturbances and control actions made to the top of vvii at at the time n. A set of realizations of impulse processes is the time n. A set of realizations of impulse processes is called "scenario" and points to the possible called "scenario" and points to the possible developments of situations. The situation is developments of situations. The situation is characterized by a pulse simulation set {characterized by a pulse simulation set {ХХ, Q} in each , Q} in each step of modeling.step of modeling.

)()()()1(1

1

nQnPfnxnx i

l

jjijii

(5)

44.1.Impulsive modeling .1.Impulsive modeling scenarios for the system on scenarios for the system on cognitive modelscognitive models

A model of a pulsed process mapping A model of a pulsed process mapping scenarioscenario

The taskThe task::3. Scenario analysis3. Scenario analysis

Cognitive Mechanisms for Decision Making Cognitive Aspects of Information Technologies Development

and Using


2424

A - matrix of relations of the graph G; A - matrix of relations of the graph G; I - identity matrixI - identity matrix

nnnn QARXX 1

1212

01 ...

nnnn

n IQAQQAQAR

where:where:

(6)(6)

The algorithm is based on a puls simulation The algorithm is based on a puls simulation calculation formulas (6), obtained from the calculation formulas (6), obtained from the expression (5):expression (5):


Using


2525

44.2. .2. Stability Stability analysisanalysis

SustainabilitySustainability ( (Known TheoremsKnown Theorems))

(1)(1) Vertex V Vertex Vjj is stable in value, if the sequence of values |(x (t):| t = 0,1, ...) is stable in value, if the sequence of values |(x (t):| t = 0,1, ...) is bounded. is bounded.

Vertex VVertex Vj j is resistant to disturbance, if the sequence of pulses is limited to is resistant to disturbance, if the sequence of pulses is limited to |(r|(rjj (t):| t = 0,1, ...). (t):| t = 0,1, ...). A weighted digraph is resistant to perturbation (value) if every vertex has A weighted digraph is resistant to perturbation (value) if every vertex has

this property. this property.

(2) Theorem on the stability of the perturbation(2) Theorem on the stability of the perturbation . A weighted digraph . A weighted digraph G, the characteristic values are different, it is resistant to perturbation G, the characteristic values are different, it is resistant to perturbation for the propagation of any disturbance if and only if every characteristic for the propagation of any disturbance if and only if every characteristic value of G modulo at most one.value of G modulo at most one.

(3) Theorem on the stability of the initial value(3) Theorem on the stability of the initial value . A weighted digraph . A weighted digraph G is stable in the initial value for a simple process of propagation of the G is stable in the initial value for a simple process of propagation of the perturbation if and only if the digraph G is stable to perturbations, for a perturbation if and only if the digraph G is stable to perturbations, for a simple process of propagation of the perturbation and the unit is not a simple process of propagation of the perturbation and the unit is not a characteristic value of G.characteristic value of G.

The system is called The system is called structurally stablestructurally stable if the topological nature of if the topological nature of the trajectories of all systems close to it is the same as a the trajectories of all systems close to it is the same as a standard.standard.

The taskThe task::5. Analysis of 5. Analysis of sustainabilitysustainability


Using

CML-2010, CML-2010, DubrovnikDubrovnik

2626

Structurally stableStructurally stableOdd loop (positive feedback) has a positive product of signs of all of its constituent arcs, odd (negative feedback) - negative

Odd cycle is the simplest model of structural instability, as any change in the initial parameter in any of its top leads to unbounded growth module parameters vertices cycle

Any change in the parameter of any vertex of odd cycle only leads to the oscillation parameters of peaks The vertex xi is absolutely stable for a given pulse process, if the sequence of absolute values of the parameters in the top (| xi (n) |; n = 0,1 ...) is bounded

Figure Figure 55..

Figure Figure 66..

Figure Figure 77..Cognitive Mechanisms for Decision Making Cognitive Aspects of Information Technologies Development and

Using


2727

ExamplExamplee

Figure 8.Figure 8.

4.3. 4.3. Topological analysisTopological analysis

01101

00000

01001

10100

01010

5

4

3

2

1

54321

GR

V

V1V3

V5

V2

V4

V2

V3 524

131

21

11 ;;;; XKY

Figure 10.Figure 10.

112;11 V2

V4

112;21 V3 V5

110;41

112;31 V1V4

V1 V4

V3

213;52

Figure 9.Figure 9.

The taskThe task::8. Connectedness, complexity8. Connectedness, complexity


Using


2828

4.4.Model decision problems: the problem of the 4.4.Model decision problems: the problem of the optimum valueoptimum value

dcdYdttMYfYCtMS

hh ,,..,

khtXM h ,...2,1,,

X Xдоп ; Y Yдоп

where φ (Mh, t) - function of the effectiveness of the optimum value of the parameters Mh distribution of random variables Y and time t; f (Y, Mh, t) - density of Y, C (Y) - useful areas S values Y. +

(7)(7)

The taskThe task::15. Decision-15. Decision-makingmaking


Using


2929Cognitive Mechanisms for Decision Making Cognitive Aspects of Information Technologies Development and

Using


55.. The scheme The scheme of interrelated techniques of interrelated techniques of cognitive methodologyof cognitive methodologyand Software system of and Software system of

cognitive modelingcognitive modeling

3030

I StageBlock 1. Definition and formalization of the setting research objectives process and decision-making on sustainable development of complex system

Results: A cognitive draft of the investigated problem, the development of studying meta-model (1)

Block 2. Is the first stage of cognitive structuring. Retrospective study. Diagnosis of the socio-economic system for correspondence with noospheric trends in accordance with the first and second requirements of sustainability

Results: The cognitive picture of the problem (retrospection is a systematic description of the object, structure and composition of the socio-economic system characteristics, correlation of the socio-economic characteristics in socio–economic, political, ecological systems of the region; diagnosis is a result of comprehensive analysis of the object forming the basis of a predictive model of the region, a conclusion about stability and the noospheric tendency of the region development

II, III Stage

Block 3. Is the second stage of cognitive structuring. Development of hierarchical cognitive models of individual subsystems of the socio-economic mechanism in the region is the identification of the object in the environment

Results: Hierarchical cognitive model of social and economic system, integrated and detailed; visualization of the results

Block 4. Is the third stage is the interrelated systemic tasks solution (cognitive modeling). Analysis of the cognitive models structure, controllability and stability of the system, pulse modeling, the study of the sensitivity of the model, updating of the model

Results: Adjusted cognitive model intended for prediction, management and decision-making. Characteristics of the model connectivity features on the basis of a simplicial analysis, the conclusion of the stability, the possible scenario developments

Block 5. Working out strategies of stable and safety development of socio-economic system variants

Results: Recommendations for of strategy of stable development realization and proposals for appropriate management mechanism forming

Scheme Scheme of of cognitive cognitive modeling modeling of socio-of socio-economic economic systemsystem



31

C

O

G

N

I

T

I

V

E

M

O

D

E

L

I

N

G

1. Cognitive construction, interactive mode

Input model

2. Structure of the cognitive model analysis

Input statistics, data processing and data analysis

E

X

P

E

R

T

3. Stability analysis(structural, to the disturbance, to the initial values)

Analysis of simplicial complexes

Searching the ways of a given type

Search for connected components

The establishment of relations between factors and to establish the nature of these relations

Input factors

Search and analysis of cycles

5. The model adjustment

Analysis of Sensitivity of the model

4. Impulsive modeling

Analysis of evolutionary development, planningof the experiment

The task of managing impacts and the moments of their depositing

Change the topological structure of the model

7. All results analysis and comparison, decision making, recommendations development

6. The choice of admissible development scenarios, the inverse problem solution, recommended solutions economic justification

Indicators of change

Change attitudes

Figure Figure 112.2.

Software Software system of system of cognitive cognitive modelingmodeling(ПС КМ)

CML-2010, CML-2010, DubrovnikDubrovnik

3232

6. 6. Examples Examples of cognitive modelingof cognitive modeling


Using


3333

«Socio-economic mechanism at the regional level»


Example №1.While identifying the object was originally developed bigger cognitive map, the objects which in the future if necessary, turned in the individual cognitive maps. For example, in the enlarged map of regional socio-economic mechanism of object "industrial output" can be discovered in the cognitive maps, and includes cognitive map "Small Business«


Using


3434

Pulse processes while bringing disturbance in Pulse processes while bringing disturbance in node Vnode V22 (manufacture growth), q (manufacture growth), q22=+1=+1

q2 =+1


Charts are located in such a way that the beginning of the pulse process for them was at the same level (for ease of analysis of images)


and Using


3535

Pulse processes while bringing Pulse processes while bringing disturbance in node disturbance in node qq22=+1, q=+1, q77=+1=+1 (manufacture growth, interregional and foreign (manufacture growth, interregional and foreign

exchange)exchange)



and Using


3636

Figure 16. Pulse processes while Figure 16. Pulse processes while bringing disturbance in node bringing disturbance in node qq99=+1 =+1 ((PopulationPopulation growth)growth)


Using


3737

Modeling System “Modeling System “SSmall mall business"business" Small business is one of the major reserves of Small business is one of the major reserves of

dynamic economic development of regions of the dynamic economic development of regions of the Southern Federal District, as the prevailing Southern Federal District, as the prevailing economic structure and the redundancy of labor economic structure and the redundancy of labor resources of individual regions objectively resources of individual regions objectively determine the possibility of development of this determine the possibility of development of this sector. Of particular importance to this segment of sector. Of particular importance to this segment of the economy has to meet the challenges of the economy has to meet the challenges of sustainable and sound development of the region, sustainable and sound development of the region, providing employment, crime prevention, solving providing employment, crime prevention, solving local government in light of the Federal Law "On local government in light of the Federal Law "On General Principles of Local Self-Government in the General Principles of Local Self-Government in the Russian Federation» № 131-FZ of 06.10.2003gRussian Federation» № 131-FZ of 06.10.2003g

Example №2.


and Using


3838

Cognitive map "Small Business"



Using


3939

V00

V12 V10

V06

V01

V08

V09

V05

V03V02

V04

V15

V14

V13

V11

Analysis of simplicial complexesAnalysis of simplicial complexes "Small "Small Business"Business"

V00V00 - Number of small - Number of small enterprises enterprises V01V01 - Investitsii MP - Investitsii MP V02V02 - Turnover MP - Turnover MP V03V03 - Number of employees at - Number of employees at the MP the MP V04V04 - Profit MP - Profit MP V05V05 - Quality products, services, - Quality products, services, MP MP V06V06 - Innovations - Innovations V07V07 - Professional quality - Professional quality employees employees V08V08 - Consumer demand - Consumer demand V09 V09 - Competition - Competition V10V10 - Availability of credit - Availability of credit V11V11 - Infrastructure - Infrastructure V12V12 - NGO programs support the - NGO programs support the development of MPdevelopment of MPV13V13 - Imperfect tax system - Imperfect tax system V14V14 - Corruption - Corruption V15V15 - Administrative barriers - Administrative barriers

The concepts of cognitive maps «Small business» (MP):



Using


4040

The cognitive The cognitive maps "Regional maps "Regional socio-economic socio-economic system in terms system in terms of adaptation of adaptation peoples of peoples of southern Russia southern Russia to the to the transformationatransformational change"l change"


Example №3.


Using


4141

V0 - sustainable development of the region,V1 - successful adaptation of peoples, V2 - An individual's ability to adapt,V3 - resources adaptation capacityV4 - economic conditionV5 - social status V6 - globalization,V7 - regionalization,V8 - geopolitical factorsV10 - a violation of cultural traditions and imposition of new,V11 - demographics,V12 - national and ethnic structure of population

V13 - ethnic hierarchy of the urban populationV14 - social organizations of Southern RussiaV15 - Islamic organizations V17 - Cossack society V18 - Diaspora V19 - conflict-generating,V20 - class contradictions V21 – youthV22 - scientific and educational complex south of Russia,V23 - authorities V24 - territorial featuresV25 - deviant behavior,V26 - media V27 - clan,V28 – migration

The concepts of cognitive maps "Regional socio-The concepts of cognitive maps "Regional socio-economic system in terms of adaptation peoples economic system in terms of adaptation peoples of southern Russia to the transformational of southern Russia to the transformational change"change"


Using


4242

Scheme of interaction models of computing Scheme of interaction models of computing devices, tasks and expertdevices, tasks and expert

МВЗ={ФGВ,ФGЗ,E}

ФGВ GВ, XВ, FВ ФGЗ GЗ, XЗ, FЗE

Q Y

МЭ = {Q, W, ПР}


ФGВ = <GВ, XВ, FВ> - a model of computing devices in the form of a parametric functional Ф -graph, in which:GB = <VВ,EВ> - cognitive map, graph in which verticesVe = (vВi) - the set of vertices agents (individual computers), EВ = (eВij) - the set of arcs

connecting the vertices (vВi, vВi vВj), i, j = 1,2, ... nВ;Arriving at the input VU task - oriented acyclic functional Ф -graphGЗ = <VЗ, EЗ> - a model problem where VЗ = (vЗi) - the set of vertices (separate tasks or parts of them), EЗ = (eЗij) - the set of arcs connecting the vertices (vЗi, vЗj), i, j = 1,2, ... nЗ;MВЗ = (ФGВ, ФGЗ, E) - a model of interaction of the ВС graph and graph problems E = (eВiЗj) - the set of arcs connecting the vertices of problems with the vertices of a graph of computing devices; Q, X = (xi), i = 1,2 ,..., k - input system (factors);Y = (y1 ,..., yi ,..., ym) - output of the system, the numerical characteristics of the purposes of the study ("optimization", "optimization criteria," "objective function »...)

Example №4.


Using CML-2010, DubrovnikCML-2010, Dubrovnik

4343

ReferenceReferencess

[Koptyug[Koptyug,, et al.et al., 2000], 2000] New paradigm jf Russia's development in the XXI century New paradigm jf Russia's development in the XXI century (Comprehensive analysis of the problems of sustainable development: ideas (Comprehensive analysis of the problems of sustainable development: ideas and results)/ Ed. V.A. Koptyug, V.M. Matrosov, V.K. Levashov. M.: and results)/ Ed. V.A. Koptyug, V.M. Matrosov, V.K. Levashov. M.: "Academia", 2000, 416 pp."Academia", 2000, 416 pp.

[Maksimov,[Maksimov, 2001. V.I]2001. V.I] V.I. Maksimov Cognitive technology - from ignorance to V.I. Maksimov Cognitive technology - from ignorance to understanding / Sat. Proceedings 1 st International Conference "Cognitive understanding / Sat. Proceedings 1 st International Conference "Cognitive analysis and development management situations", (SASC'2001) - Moscow: analysis and development management situations", (SASC'2001) - Moscow: IPU RAN, 2001. - Vol.1, pp 4-18IPU RAN, 2001. - Vol.1, pp 4-18

[Abramova[Abramova et al.et al., 2006], 2006] The human factor in management. Ed. N.I. Abramova, KS The human factor in management. Ed. N.I. Abramova, KS Ginsberg, D.A. Novikov. - M.: KomKniga, 2006.Ginsberg, D.A. Novikov. - M.: KomKniga, 2006.

[Roberts[Roberts, 1978] Roberts F, 1978] Roberts F.. Graph Theory and its Applications to Problems of Graph Theory and its Applications to Problems of Society, Society for Industrial and Applied Mathematics, Philadelphia, 1978.Society, Society for Industrial and Applied Mathematics, Philadelphia, 1978.

[Gorelova[Gorelova et al.et al., 2002], 2002] Gorelova G.V., Dzarimov N.H., Acceptance of Decisions on Gorelova G.V., Dzarimov N.H., Acceptance of Decisions on the Cognitive Cards of Socially-Economic Systems// IEEE International the Cognitive Cards of Socially-Economic Systems// IEEE International Conference on Artificial Intelligence Systems (ICAIS 2002), Divnomorskoe, Conference on Artificial Intelligence Systems (ICAIS 2002), Divnomorskoe, Russia. – Computer city: IEEE, 2002. – № 7996-1733. – Russia. – Computer city: IEEE, 2002. – № 7996-1733. – ррp. 128-129. p. 128-129.

[Gorelova[Gorelova et alet al.., , 2002,Gorelova, 2002,Gorelova, et al.et al., 2006], 2006] Gorelova G.V., Zaharova E.N., Gorelova G.V., Zaharova E.N., Radchenko C.A. Researches of semi-structured problems for social-Radchenko C.A. Researches of semi-structured problems for social-economical systems:Cognitive approach. – Rostov: RGY, 2006.economical systems:Cognitive approach. – Rostov: RGY, 2006.

[Atkin[Atkin, , 1997]1997] Atkin R. H. Combinatorial Connectivies in Social Systems. An Atkin R. H. Combinatorial Connectivies in Social Systems. An Application of Simplicial Complex Structures to the Study of Large Application of Simplicial Complex Structures to the Study of Large Organisations, Interdisciplinary Systems Research, 1997.Organisations, Interdisciplinary Systems Research, 1997.

[Barcelo[Barcelo, , et alet al.., , 1998]1998] Barcelo H., Kramer X., Laubenbacher R., Weaver C. Barcelo H., Kramer X., Laubenbacher R., Weaver C. Foundations of Connectivity Theory for Simplicial Complexes, Department of Foundations of Connectivity Theory for Simplicial Complexes, Department of Mathematical Sciense, New Mexico, 1998Mathematical Sciense, New Mexico, 1998

[Mnukhin[Mnukhin, , 1996]1996] Mnukhin V. The Modular Homology of Inclusion Maps and Group Mnukhin V. The Modular Homology of Inclusion Maps and Group Actions, J. of Combinatorial Theory, S. A 74, 1996, pp.285-300, Article NO. Actions, J. of Combinatorial Theory, S. A 74, 1996, pp.285-300, Article NO. 00510051

[John Casti,1979][John Casti,1979] John CastiJohn Casti Connectivity, Complexity, and Catastrophe in Large-Connectivity, Complexity, and Catastrophe in Large-scale Systems. /A Wiley –Iinterscience Publication– International Institute for scale Systems. /A Wiley –Iinterscience Publication– International Institute for Applied Systems Analysis. - Chichester- New York- Brisbane- Toronto: John Applied Systems Analysis. - Chichester- New York- Brisbane- Toronto: John Wiley and Sons, 1979Wiley and Sons, 1979

4444

TheThe results of the various phases of studies consistently reported at conferences, published in journals and monographs.

This report is a certain generalization of the results and reflections on the theme of "cognitive modeling of complex systems"


Using


45

4646

Thank you for your attention!Thank you for your attention!

Galina GorelovaTechnological Institute

at South Federal University, Taganrog

Nekrasovskiy 14, 347922, ГСП 17-А Russia

[email protected]


mailto:[email protected]

47

48

49

50

COGNITIVE MODELING AS A TOOL IN THE PROCESS OF KNOWLEDGE LARGE SYSTEMS Galina Gorelova CML-2010, Dubrovnik Cognitive Mechanisms for Decision Making Cognitive.

Documents

systems analysis

ecological systems

intelligent systems

utilization of systems

dubrovnik cognitive

development of governance

cognitive modeling technology

complex problem