www.b-b.by THE HERITAGE OF H.S. Altshuller, creator of TRIZ-RTV-TRTL. Help on the Inventive Problem Solving Algorithm. Help on Inventive Problem Solving Theory. TEXTBOOK TRIZ V. PETROV FOUNDATIONS OF TRIZ. (M.S. Rubyn) Igor Vikentiev about the creator of TRIZ H.S. Altshuller.
www.b-b.by Encyclopedia of TRIZ. International Association TRIZ  (MATRIZ) Business Association TRIZ. ETRIA is the European TRIZ Association. International public organization 'TRIZ Developers Summit'. Methodologist - the site is dedicated to inventive problems and methods of their solution.
ALGORITHM INNOVATIVE TECHNOLOGICAL CONSULTING NPK JSC is a consulting bureau with an integrated and innovative approach to building business processes.

   The programs "MODIFIER", "M.Light", "Functional Analysis in TRIZ", "Idea Generator", "IMPACTS IN TRIZ", "CHANGING SYSTEMS in TRIZ",
created on TRIZ tools ("Theory of Inventive Problem Solving" by Heinrich Saulovich Altshuller ("Teoriya Resheniya Izobretatelskikh Zadatch")) and some other cognitive technologies. These programs are interactive guidebooks - reference books on the stages of the workflow of finding solutions to inventive tasks, problems and situations.



(Note:The program is updated periodically, so once every few weeks it is advisable to reload this page. (To do this, press the right mouse button, a context menu will appear, select the “Reload” item in it and press the left button computer mouse.)

Program: MODIFIER.    Software: M.light.    Software: Functional analysis in TRIZ.    Program: FLOW ANALYSIS IN TRIZ.    Software: Idea Generator.    TRIZ IMPACT Program.    Program CHANGING SYSTEMS in TRIZ.

   GUIDEBOOK - A REFERENCE BOOK ON THE TRIZ ECOSYSTEM AND SOME OTHER COGNITIVE TECHNOLOGIES.

   1. FACTORS necessitating CHANGES IN TECHNICAL AND NON-TECHNICAL SYSTEMS in order to fulfill emerging new human needs.

      1.1. FACTORS causing the need to CHANGE technical and non-technical systems (for the implementation of emerging new human needs) can be:

      ● Intraspecific competition between people, communities of people, objects and groups of objects of flora, fauna, as well as between several autonomous systems of Artificial Intelligence (AI) (located in information interaction among themselves) generated by the struggle for limited intangible or material values (resources) on which the achievement of their goal, their viability, well-being may depend (Konstantin Kulikov).
      ● Necessity (need) of adaptation to changing conditions of the internal or external environment in humans, communities of people, objects and groups of objects of flora, fauna, as well as for some AI systems based on neural networks or automatic control devices (based on analog or digital logic) with appropriate detectors, structures for processing the incoming information flow and creating a control information flow for actuators.
      ● Curiosity is an unconscious desire for knowledge, inherent not only to humans, but also to many living beings.
(Note: for AI systems, the state of "curiosity", when confronted with something that goes beyond the mastered knowledge (on which the neural network is trained) or contradictory ("mystery") to the established scientific paradigm, is not clearly defined.
The neural network, in such cases, generates information (images, texts, speech, ...) that is far from common human sense, creating information by mixed parts of the acquired knowledge and is not able to go beyond this knowledge to create a different principle for the functioning of the new system.
Perhaps, in this case, using the TRIZ approaches, the AI system, based on the detected feature ("contradiction" (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM)) and its detailed description, using the inductive methods and "tools" of TRIZ and the concept of operational thinking by L. Vygotsky and J. Piaget, can develop new ways to achieve the goal (solving the "mystery"), or reformat the task with the setting of a new goal).
      Won't this form of "information processing" in AI systems become the moment of the birth of a full-fledged, "strong" intelligence (the hypothesis of a technological singularity, called the "intellectual explosion" by the British mathematician and cosmologist Irving Goode).


         Curiosity - is an interest devoid of rational grain, but underlying any knowledge and being the root of desire for knowledge.
         Interest is a positively colored emotional process (according to the classification of A.N. Leontiev — feeling) associated with the need to learn something new about the object of interest, increased attention to it. It's interesting when something unexpected happens.
         Desire for knowledge leads beings who are aware of their rationality to knowledge (to unraveling various mysteries, riddles, puzzles, secrets, ...).
         Rationality (from Latin ratio - mind) is a term in the broadest sense meaning reasonableness, meaningfulness, the opposite of irrationality.

      Competing "stakeholders" form requirements for new technical or non-technical systems.
      "Stakeholders" can be markets, customers, consumers, requirements for compliance with legal, environmental, etc. laws, ....
      Such an evolution of systems can be both creative and destructive in relation to different "stakeholders".
      The successful introduction of a new technical or non-technical system into the daily activities of the company takes place along the path of least resistance (the balance of interests of the "stakeholders" is almost not violated and in this case the implementation costs are minimal).
      Artificial, forcible introduction of a new system into the daily activities of society entails large costs, losses of various kinds to overcome this resistance and it does not guarantee a long life cycle of the new system.
      In new, changed environmental or internal conditions of a technical or non-technical system, technical and other requirements of "stakeholders" for a new system can be formed through parameter values (higher or lower; more optimally measured or stabilized), different from the values of the parameters of the aging system:
pressure, vacuum, temperature, vibration, sound, speeds, rpm, electric field, magnetic field, electromagnetic field radiation of various frequencies, charged particle fluxes, profitability and labor productivity, sales of goods and services, logistics, process manageability, operational safety, etc..

      1.2. The contradictions (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) that arise in the way of implementing a project of a new (possibly optimization of an old) technical or non-technical system are not a driving factor, but a deterrent. (Konstantin Kulikov).

The main feature of inventive problems and situations is the presence of a CONTRADICTION (CONFLICT) (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) in the system, which can be eliminated by TRIZ.       Predicting a CONTRADICTION (CONFLICT) (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) - is a prediction of the possibility of a CONTRADICTION (CONFLICT) (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) in the system and the consequences of its possible development. A forecast is a representation of a future CONTRADICTION (CONFLICT) (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) in a system with a certain probability of indicating the place and time of its occurrence. Forecasting is used for systems of natural and artificial origin. For systems of artificial origin, forecasting is used most often at the stages planning, of design, testing, as well as in the event of abnormal or emergency situations. (Forecast (from Greek. πργγνωση "foresight, prediction)).
      Prevention of CONTRADICTION (CONFLICT) (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) - is an activity aimed at preventing its occurrence and destructive influence on the elements included in the system. TRIZ creator - H.S. Altshuller gives the following definition of a contradiction (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) in technical systems:
"A technical contradiction (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) is called INTERACTION (note -"interaction") in a system, which consists, for example, in the fact that a useful action causes SIMULTANEOUSLY a harmful action." CONTRADICTION (CONFLICT) (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) arises in the system during the interaction of its parts, when the same action of Subject 1 is useful for Object 1 (or Process 1) and harmful for Object 2 (or Process 2).
      Part 01. contradictions (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) 'DESIRED ACTION', useful function: What makes Subject 1 useful for Object 1 (or Process 1)?
      Part 02. contradictions (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) 'UNWANTED ACTION', harmful function, opposite function, anti-action: What does Subject 1 do for Object 2 (or Process 2) harmful?
      (If there are CONTRADICTIONS (CONFLICTS) (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM), then there must be 'TOOLS' to resolve them.)
       1.3. NOTE.
       1.3.1. A subject in philosophy is a bearer of an action, one who (or what) cognizes, thinks or acts, as opposed to an object (as what the subject's thought or action is directed to).
       1.3.2. Object (lat. «Objectum» “subject”) is a philosophical category denoting a thing, phenomenon or process to which the subject-practical, controlling and cognitive activity of the subject (observer) is directed; in this case, the subject itself can also act as an object. The subject can be a person, a social group, or an entire society. The concept of an object («obiectum») is used by Thomas Aquinas to denote what a desire, aspiration or will is directed to.
       1.3.3. Process (Latin «processus» - passage, advancement) is a category of philosophy that characterizes the totality of irreversible, interconnected, long-term changes, both spontaneous and controlled, both self-organized and organized, the result of which is some kind of innovation or innovation. Or a sequential change in a number of states of a certain phenomenon in life and in thinking, which leads to its qualitative change and transition to another phenomenon. The content of the process is characterized by such concepts as change, development, evolution, etc.
       1.3.4. Function (Latin «function» - execution, accomplishment) is a relationship between elements, in which a change in one element entails a change in another.
       1.3.5. Action - a structural unit of activity; a relatively complete separate act of human activity, which is characterized by a focus on achieving a certain perceived goal, arbitrariness and premeditation of individual activity.
       1.3.6. Dialectics (in philosophy) is a way of understanding the world in which various phenomena are considered in the diversity of their connections, the interaction of opposing forces, tendencies, in the processes of change, development.
       1.3.7. A technical system is an artificially created system designed to meet a specific need, existing:
       1.3.7.1. As a production item;
       1.3.7.2. As a device potentially ready to perform a beneficial effect;
       1.3.7.3. As a process of interaction with components of the surrounding or internal environment, which results in a beneficial effect.
       Technical systems include individual machines, devices, devices, structures, hand tools, their elements in the form of nodes, blocks, assemblies, etc.
       1.3.8. A non—technical system is a set of phenomena and processes in a non-technical field (biological, environmental, social, political, managerial, business, informational, ...) that are in relation and connection with each other, forming some non-technical object.
       A non—technical system is an integral unity, the main element of which are people, communities, peoples, states; objects of flora, fauna, ecology, biology; objects of management, business, information; ... their interactions, relationships, connections.
       These connections, interactions and relationships are stable and are reproduced in the historical process on the basis of the joint activity of the elements of a non-technical system, passing from generation to generation.

        In technical and non-technical complex systems, in order to conduct an analysis with the aim of further improving a complex system, it is necessary to build an abstract model of the system, for this, dividing the complex system into many separate parts (modules, nodes / personalities or communities).
       Each such part of a complex system has a set of its own individual properties, which are characterized by parameters that have certain physical, chemical (for technical parts of the system) or social, psychological (for non-technical parts of the system) types.
       The parameters of a separate part (module, node / personality or community) of a complex system (Subjects) that affect the parameters of another part of the system (Objects) form a set of first elements of "elementary systems" (Subjects) of different types - physical, chemical (for technical parts of the system) or social, psychological (for non-technical parts of the system).
       Parameters of a separate part (module, node / personality or community) of a complex system (Objects), perceive the impact and parameters (Subject), and form a set of second elements of "elementary systems" (Objects) of different types - physical, chemical (for technical parts of the system) or social, psychological (for non-technical parts of the system).
       the SUBJECT (characterized by many individual properties (parameters)) / affects / the OBJECT (characterized by many individual properties (parameters)).
       At the same time, two events occur in the "elementary system": Event No. 1 - the impact of the Subject (Cause) + Event No. 2 - the result, a change in any properties of the Object (Consequence). Such a relationship in the "elementary system" is called: Causal relationship.













       1.3.9. Conflictology is an interdisciplinary area of knowledge that studies the patterns of origin, origin, development, resolution and completion of conflicts of any level. The solution of a certain range of problems that cause the emergence of a conflict can help to overcome the difficulties that have already emerged in connection with the definition of the essence of the conflict, the object and subject of conflict management.
       Since the conflict is indeed a contradiction (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM), albeit of a special (illogical) kind, the analysis of both concepts is an urgent problem.
       The basic category of systems analysis is attitude. Depending on how contradictory relations relate to each other, logical and non-logical relations are distinguished, as well as various types of non-logical contradictions (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM).
       1.3.9.1. Complementary contradiction (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) - unification of relations, asymmetrical, but mutually dependent in their truth (+ and +) or (- and -) from each other.
       Example: 'Tatiana loves (+) Onegin' and 'Onegin is loved (+) by Tatiana'. Оr: ("Tatiana hates (-) Onegin" and "Onegin is hated (-) by Tatiana").
       1.3.9.2. Signal contradiction (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) - the unification of true relations, but opposite to each other (+ and -).
       Example: 'Tatiana loves (+) Onegin' and 'Tatiana hates (-) Onegin'.
       1.3.9.3. A complementary-sign contradiction (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) is formed when complementary and sign relations are combined in one system at the same time.
       Example: 'Tatiana loves (+) Onegin' and 'Onegin hates (-) Tatiana'.
       What class of contradictions (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) does the conflict belong to? It follows from the definition of a conflict that the relations that form it must represent opposites, which both deny each other, and at the same time are true together. Otherwise, when only one of the opposites is true, or when both are false, the opposition of activities in the system and thus a systemic conflict becomes impossible. This means that a conflict can be an illogical contradiction (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM), both opposites of which are simultaneously true (active).
       All three types of illogical contradiction (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) correspond to the previously introduced definition of conflict. According to each of them, the activities of the subjects turn out to be opposing and generate a state of self-inhibition of the entire system of relations, either because of the asymmetry of the relations of the subjects, or because of the opposition of the relations of the subjects to each other in direction and / or in sign.
       Based on the foregoing, it can be argued that each illogical contradiction (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) is a specific conflict and each conflict is a certain kind of illogical contradiction.
       Therefore, the following definition is valid:
       Conflict is a complementary, sign or complementary sign contradiction, in which both opposite relationships are simultaneously true.
       The most general definition of a conflict can be considered the following.
       Conflict is an imbalance in the internal and / or external relations of the system.
       Conflict is the state of the system, which indicates its inability to continue its vital activity in the same quality. Such inability means the loss of stability of the functioning of the system at a significant level for it.
       Consequently, conflict is the most important, if not the only, indicator of the system's transition from a stable state, characterized by the absence of the need to search for other forms of existence, to an unstable state, the main feature of which is the formation of an urgent need to return to the previous form of existence or create a new one.

       1.3.10. The methodology of the ARIZ and the TRIZ actively uses in practice the laws of philosophy, logic, psychology, conflictology, linguistics (lexicology, semantics).
       The German philosopher Georg Wilhelm Friedrich Hegel (1770-1831), developed a separate dialectical method of argumentation - a form and method of REFLEXIVE (REFLECTED or 'reversed', inverted) theoretical thinking exploring CONTRADICTIONS (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM).
       The philosophical category of Subject (carrier of activity, consciousness and cognition), applicable to TRIZ, is someone or something that produces a 'DESIRED ACTION' (useful function) over 'Object 1' (or Process 1) + 'UNDESIRABLE ACTION' (harmful function, opposite function, anti-action) on 'Object 2' (or Process 2).
       The subject can be a person, a social group or the whole society, an inanimate object.
       The philosophical category Object (Lat. objectum 'object') — denotes a thing, phenomenon or process that the subject's (observer's) subject-practical, controlling and cognitive activity is directed at, while the subject himself can act as an object.
       Hegel's dialectic explains the development of thinking through a triad: Thesis → Antithesis → Synthesis.
       TRIZ (creator Heinrich Saulovich Altshuller (1926-1998)) is a practical dialectic, and the development of thought in TRIZ also occurs through a triad:
       Thesis = 'DESIRED ACTION' (useful function) ('Yang' - in Chinese philosophy, '+') for Object 1 (or Process 1) →
       Antithesis = 'UNDESIRABLE ACTION' (harmful function, opposite function, anti-action) ('Yin' - in Chinese philosophy, '-') for Object 2 (or Process 2)→
       Synthesis = 'DESIRED ACTION' (useful function) + 'UNDESIRABLE ACTION' (harmful function, opposite function, anti-action).
       The first law of dialectics, the unity and struggle of OPPOSITES (polar actions, forces), concerns the transition of things and ACTIONS, in the process of their development, into their opposite (REFLECTION or 'turning back', inverting).
       OPPOSITES are those sides that always exclude each other, complement each other and are in inseparable unity.
       A CONTRADICTION (CONFLICT) (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) arises between two diametrically OPPOSITE ACTIONS: 'DESIRED ACTION' (useful function) ↔ 'UNDESIRABLE ACTION' (harmful function, opposite function, anti-action).
       The sharpness of the CONTRADICTION (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) that manifests itself between two diametrically OPPOSITE ACTIONS (FUNCTIONS) is directly proportional to the duration of their meeting (contact) with each other.
       Finding the root cause of the contradiction (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) clarifies the task and indicates the direction of further work.
       There can be many levels of contradictions (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM), so identifying cause-and-effect relationships is a search for the root of the problem, the main reason why this contradiction (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) arose.
       The level of contradictions (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) are divided into:
       - the most superficial (administrative or others) - the contradiction (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) between the need and the possibility of satisfying it.;
       - a more in-depth (technical or others) is a contradiction (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) between certain parts, qualities or parameters of the system;
       - aggravated, even more in-depth (physical or others) - presentation of diametrically opposite properties (for example, physical or others) to a certain part of a technical or non-technical system.

     Logic as a science has developed over two and a half millennia and has given rise to entire groups of logics (Classical, Mathematical, Non-classical, Philosophical), which combine many different logics.

     "De facto" Heinrich Saulovich Altshuller created "LOGIC CLASS elimination (bypass, avoidance) of the contradiction (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) (conflict) existing in the system", which, with the appropriate mathematical formalization, should take its place in science (perhaps in the group of Non-classical logics). At present, work on the development, formalization, practical application of this type of logic for solving specific problems is being continued by his students, colleagues and followers in many countries.

       THE UNITY of diametrically opposite ACTIONS (FUNCTIONS) lies in the fact that they have the same source of origin - the Subject (without the Subject, ACTIONS (FUNCTIONS) are impossible).
       A unique feature of the methodology and logic of solving the problem in ARIZ is that a logical model ('logical framework') of solving the problem is formed, in which initial REAL data are introduced and final HYPOTHETICAL (DESIRED) data and parameters are formed, such as:
       - 'DESIRED ACTION' (useful function) and 'UNDESIRABLE ACTION' (harmful function, opposite function, anti-action);
       - Subject, is it someone or something who performs these two diametrically OPPOSITE ACTIONS;
       - Objects or processes affected by the Subject, their parts, properties, fields, methods, attributes, etc.;
       - CONTRADICTION (CONFLICT) (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) that arises between these two diametrically OPPOSED ACTIONS;
       - Aggravation of a CONTRADICTION (CONFLICT) (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM), inversion of an 'UNDESIRABLE ACTION' (harmful function, anti-action) into a neutral or useful ACTION (function);
       - Formation of a hypothetical Ideal Final Result (IFR);
       - Formation of requirements for the parameter of the X-element (Subject-modifier) - substance or method (function) (it can be - substance, physical field / energy / effect, time intervals, chemical bond / energy / effect, mathematical / engineering / technical method, method from other fields of knowledge));
       At this stage, the formation of a logical model ('logical framework') for solving the problem is completed.
       This is followed by the stage of searching for the parameter of the X-element (Subject-modifier) by the techniques, means and 'tools' of TRIZ.
       The solutions found are evaluated for their closest approximation to the Ideal Final Result (IFR), as well as the possibility of practical implementation and acceptable cost. And finally, the final choice of an acceptable solution is made.

       1.3.11. The best methods of activating creativity.









    2. STEP-BY-STEP CYCLE OF SOLVING THE PROBLEM.

   2.1. Identification of the problem and understanding of the situation.

The purpose of a new or optimized old system is to increase any positive effect.
But, in the real world, at some stage (design, testing, implementation, development of an emergency situation, changes in external conditions), an undesirable effect occurs (harmful, destructive, reducing profitability and labor productivity, falling sales of goods and services, deterioration of logistics, deterioration of process manageability, violation of operational safety, etc.)).

   2.2. Documentation, goal setting and planning.

The study of a technical (or non-technical) system allows you to fix obstacles and inefficient solutions that exist in the system, and also carry out further planning of actions to find effective solutions..

   2.3. Decomposition of the selected task, division into separate subtasks (the output of one subtask is the input data for another subtask, etc.). The breakdown of a complex system into interconnected "elementary systems" (construction and definition of links of "chain links" of CAUSE-EFFECT RELATIONSHIPS).

Data collection, analysis and hypothesis testing.
Description of the system at the abstract level, identification of the conflicting pair, description of the contradiction (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM), formulation of the Ideal Final Result (IFR) (TRIZ).

   2.4. Synthesis - generation of ideas for solutions.

Application of templates to solve the problem using methods and "tools" of TRIZ.

   2.5. Evaluation and selection of the optimal solution idea satisfying the specified requirements from a finite set of solutions found.

   2.6. To evaluate the evolutionary potential of the system based on empirical patterns of system development and to work out possible ways of further evolution of the system in question.

   2.7. Evaluate the various risks associated with the practical implementation of the solution, whether they can be reduced or completely avoided.


   3. FORMS OF IDEA MANAGEMENT (ABSTRACT CONCEPTS).

It is traditionally believed that the discovery of a new pattern is an example of inductive (heuristic) thinking, largely due to intuition.

With the development of such sciences as philosophy, logic, cognitive psychology, the psychology of creativity, as well as the study of various teaching methods and the operation of artificial neural networks, it became possible to better understand the forms of thought processes at various stages of creativity.

(Reference: Cognitive science, cognitive science (lat. cognitio "knowledge") is an interdisciplinary scientific direction that combines the theory of knowledge, cognitive psychology, neurophysiology, cognitive linguistics, non-verbal communication and the theory of artificial intelligence. Refers to transdisciplinary research, interdisciplinary science , cognitive science).

At various stages of solving a problem, methods can be used, which are various forms of managing methods of cognition, logical conclusions, ideas (abstract concepts).

DEDUCTIVE METHODS (with partial "interspersing" of INDUCTION METHODS) used in TRIZ narrow the scope of the solution search to certain limits, which allows you to quickly optimize the existing system, increase its positive effect and reduce, neutralize or eliminate negative properties (On the Altshuller H.S. scale - 1, 2, 3 levels of solution quality - inventions).

    3.1. Deduction, Deductive logic (inference, from general to particular, consequences are derived from accepted hypotheses ('something' must be));

The doctrine of how to acquire reliable knowledge was systematized by Aristotle (384-322 BC) in the form of the science of knowledge, deductive logic or "Classical Logic".

Aristotle owns the doctrine of scientific proof, set forth in his work "Organon" - a universal instrument of true knowledge.

Deduction (derived from the Latin word: deductio - conclusion).

Deduction is a logical and methodological procedure by which the transition from GENERAL to PARTICULAR is carried out in the process of reasoning. (Rational form of thinking).

A logically correct conclusion from already existing knowledge or from already existing thoughts) in the process of reasoning - from the accepted hypothesis the Consequence is deduced: “SOMETHING” must be. The general underdevelopment of the experimental sciences (empirical knowledge) of that time prevented us from recognizing such a method of knowledge as incomplete induction as the main one. Usually, it is believed that Aristotle recognized only complete induction, and underestimated the incomplete one. (See Fig. 1.)

Deduction is a logically correct conclusion from already existing knowledge or from already existing thoughts, which is often used in standard education and activities little related to creativity.
(For example, the executor works according to unambiguously specified: in education - training programs; in production - technological maps; in administrative and bureaucratic activities - a system of legislative acts and official instructions; in paramilitary structures - service regulations, instructions, orders; ...).

Deduction
Figure. 1. Fresco by Raphael Santi "The School of Athens".
The central figures are: Plato pointing to the sky and Aristotle pointing to the earth.

   Table 1.Deductive method for "NonTechnical" Systems (subject to exact execution).
Deductive method for 'NonTechnical' Systems

   Table 2. Deductive Method for "Technical" Systems. (See Fig. 2, 3).
Deductive method for 'Technical' Systems

'ELEMENTARY' SYSTEM, TECHNICAL
Figure. 2. "ELEMENTARY" SYSTEM, TECHNICAL - A system that is maximally simplified for the purpose of convenience of research;
considered as a whole, the formalization of some really existing or projected System (ES element can also be a PROCESS).

'ELEMENTARY' SYSTEM, TECHNICAL

Figure. 3. In ARIZ, for research, a part of a complex system is selected, which is 2 “elementary” Systems (2 “links” in the CHAIN OF CAUSE AND EFFECT RELATIONS) (ES element can also be a PROCESS).

The 2 “elementary” Systems under consideration have a common Subject and 2 Objects:
● The 1st "elementary" system produces the desired action for Object 1. (Positive effect + : Subject affects Object 1).
● The 2nd "elementary" system produces an undesirable action for Object 2. (Negative effect - :Subject affects Object 2).

Between the two results (Consequences 1 and Consequences 2) in 2 systems, there is a contradiction (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) (both Consequences are determined).

(The formulation of a contradiction (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) is possible only when deductive logical conclusions are formed in both "elementary" technical systems.)
An algorithmic way is used, a deductive logical inference, used in some TRIZ methods, when solving problems.

An exception are interactions in quantum mechanics:
quantum effects are mainly manifested at microscopic scales and the predictions of quantum mechanics
may differ significantly from the predictions (Consequences) of classical mechanics.

An element of an “elementary” System can play the role of a Subject when it acts on an Object, and vice versa,
it can also play the role of an Object when it is affected by another Subject.

'ELEMENTARY' SYSTEM, TECHNICAL - answer

Figure. 4. In the process of finding a solution in ARIZ, in order to turn a negative effect into a positive one (for Object 2) and elimination of contradiction (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM), an impact is applied on Subject (ES element can also be a PROCESS).       Such an impact could be: X - an element (subject, modifier), this is a substance, a physical field/energy/effect, a chemical bond/energy/ effect, mathematical/engineering/technical method, method from other fields of knowledge, or a combination of methods, substances, information.

      For complete determinism of the results, a transition, where possible, to a complete formalization of deductive methods in terms of mathematical logic is necessary. For technical Systems in ARIZ, the initial formal description in terms of first-order logic may look like this:

     *WFF G1: P(f(S), O1), true. P (Positive) - a predicate that reflects the desired effect of the Subject (S) on the Object 1 (O1) (Cause / Effect).
(*, where (WFF) - Well-Formed Formula).

      WFF G2: N(f(S), O2) , true. N (Negative) - a predicate that reflects the undesirable effect of the Subject (S) on the Object 2 (O2) (Cause / Effect). A contradiction (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) arises between the predicates P and N, the same Subject performs the desired action on Object 1 and the undesirable action on Object 2.

      WFF G3: M(f(SX), S), true. M (Modifer) - a predicate that reflects the modifying effect of the Subject X (SX) (Cause) on the Subject (S) (Consequence), to eliminate the contradiction (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) between the predicates P and N.

      WFF G4: M(f(SX), S) ⋀ N(f(S), O2) → MN(f(SSX), O2), true. MN (Modification Negative) - a new predicate that displays the conjunction of two predicates M(f(SX), S) and N(f(S), O2) , which takes the value "true" for some desired values of SX from the set.
Т , at which the predicate N(f(S), O2) takes the value "false". The truth set T for a predicate is the intersection of the truth set of the predicate M(f(SX), S) - T1 and the set of false values N(f(S), O2) - T2, that is, T = T1∩T2.

      WFF G5: MN(f(SSX), O2) ≡ ¬N(f(¬S), ¬O2), true, logical equivalence or equivalent, reflects the achieved positive result.

    3.2. Induction ,
JOHN FREDERICK WILLIAM HERSHEL ON INDUCTION (1792–1871) ,
Mill's Methods Of Induction (1806–1873) ,

      Induction - guidance, prompting, from the particular to the general, empirical testing of hypotheses or consideration of hypotheses and measuring the degree of their agreement with the facts ('something' really exists, probabilistic logic, confirmation logic).

The inductive method of cognition, inductive logic (Bacon's Method) - was introduced by the English philosopher, historian, publicist, statesman, founder of empiricism and English materialism Francis Bacon (1561-1626), in his essay "The Great Instauration" and "New Organon" (1620).

Dissatisfied with the state of the sciences of his time, Bacon attempted to update the way of studying nature, which would not only make the existing sciences and arts more reliable, but also made it possible to discover new ones, still unknown to mankind.

He contrasted the dogmatic deduction of the scholastics with the inductive method based on a rational analysis of experimental data.

"The New Organon" became the second part of the extensive work "The Great Restoration of Sciences", which, according to Bacon's idea, should consist of six parts. However, the author has finished only the first two parts.

F. Bacon F. Bacon, congress
Figure 5. Francis Bacon in a portrait by John Vanderbank and a monument to Francis Bacon at the US Library of Congress..

Subsequently, a huge contribution to the development of inductive methods was made by such scientists as (See Fig. 6):
John Herschel, John Stuart Mill, William Whewell, Augustus de Morgan, William Stanley Jevons, Pierre-Simon de Laplace.

Scientists
Figure. 6. From left to right:
JOHN FREDERICK WILLIAM HERSHEL (1792-1871), JOHN STUART MILL (1806-1873), William Whewell (1794-1866),
Augustus de Morgan (1806-1871), William Stanley Jevons (1835-1882) , Pierre-Simon de Laplace (1749-1827).

Induction (from Latin inductio - prompting (guidance)) is a term widely used in science.

The essence of inductive analysis of facts boils down to the fact that through the study of various kinds of RELATIONSHIPS phenomena ("Processes") in a real-life or thought experiment, to discover their true causal relationships and dependencies on each other.

The main task of the science of nature (similarly - technical or non-technical system) is to study the causal relationship of phenomena ("Processes"), and not just their material composition - the number and properties (parameters) of "Objects".

In inductive logic, the task is to find general forms of phenomena ("Processes"), and not their specific differences.

In this teaching, Francis Bacon adheres to the philosophy of Aristotle and by the forms of phenomena ("Processes"), he means those general laws or typical relations of phenomena, to the discovery of which all experimental science strives.

The inductive method is used when there are no GENERAL algorithmic solutions.

The inductive method is a method of research and presentation, in which from the observed PARTICULAR facts one proceeds to the allocation of principles, GENERAL provisions of the theory, the establishment of regularities.

Induction is a type of GENERALIZATION associated with anticipating the results of observations and experiments based on experience data (PARTICULAR data).

In induction, the data of experience (PARTICULAR data) "suggest" the GENERAL, therefore inductive GENERALIZATIONS are usually considered as experimental truths or empirical laws.

Induction is a term widely used in science. Induction - (introduction, guidance, from particular to general, empirical testing of hypotheses put forward or consideration of hypotheses and measuring the degree of their agreement with the facts. “SOMETHING” really exists, probabilistic logic is used, confirmation logic is used.

HEURISTIC PROBLEM SOLVING - a problem solving path that includes a practical method that is not guaranteed to be accurate or optimal, but sufficient to solve the problem, it involves the use of an INDUCTION method (an inference process based on the transition from SPECIAL to GENERAL FEATURES (See. Fig. 7.)).
'ELEMENTARY' SYSTEM, NOT TECHNICAL
Figure. 7. "ELEMENTARY" SYSTEM, NOT TECHNICAL (ES element can also be a PROCESS).

In some TRIZ methods, when solving problems, a logical inference based on incomplete induction is used.
Methods of fuzzy logic theory and the like are used for Event 2 and are designed to calculate the result (Conclusion, Consequence), the occurrence of which has the highest probability from the set of options.

The inductive method is used when there are no GENERAL algorithmic solutions.
The inductive method is a method of research and presentation, in which one moves from the observed SPECIAL facts to the selection of principles, GENERAL provisions of the theory, the establishment of patterns.
Induction is a conclusion from facts to some hypothesis (general statement, patterns).
Inductive conclusions are built on the basis of experimental data. Depending on the completeness and completeness of the experience underlying the generalizations, a distinction is made between complete and incomplete induction.

Full induction - when the generalization refers to a finitely visible field of facts.
The conclusion of the full induction gives certain knowledge.
In full induction the conclusion is connected with necessity, not with some probability, and follows from premises.
Thus, this "full induction" is a kind of deductive reasoning, although in its external form, in the course of thought it resembles incomplete induction.
Incomplete induction - when the generalization refers to an infinitely or finitely - boundless field of facts.
The conclusion of incomplete induction gives probabilistic knowledge.

Incomplete induction - the incompleteness of the inductive generalization is expressed in the fact that not all, but only some elements, or parts of the class are examined.
In inductive logic, the task is to find general forms of phenomena ("Processes"), and not their specific differences.
The probability of a conclusion in a given scheme, therefore, can range from very small to almost complete certainty.
Due to this fact, in incomplete inductive logic, special methods for estimating the probability of conclusions are developed.

General knowledge, in comparison with the totality of disparate knowledge about individual objects of a class, is valuable in that it can suggest that there is some connection between the objects of the class and the attribute, and thus stimulate further knowledge.

Incomplete induction is divided into two types:
a) Incomplete "popular" induction enumerative (through enumeration of similar cases) , (induction by simply listing similar cases, generalization is carried out on an insignificant basis), in the absence of a contradictory case, is not reliable, so the greater the number of premises, the higher the probability of the conclusion. Popular induction is the first step in the development of scientific knowledge. Science begins with empirical research, classification, identification of stable connections, relationships and dependencies. The first generalizations in science are due to the simplest inductive conclusions through a simple enumeration of recurring features. They perform an important heuristic function of initial assumptions, conjectures and hypothetical explanations that need further verification and clarification. In conditions where only some representatives of the class are studied, the possibility of a hasty generalization is not ruled out. Erroneous conclusions in the conclusions of popular induction may appear due to non-compliance with the requirements for accounting for contradictory cases, which make the generalization untenable. Of the many phenomena, he fixes only those that turn out to be predominant in experience, and builds a hasty generalization on their basis.

b) Scientific induction (incomplete) (the transition to general knowledge is made on the basis of identifying the necessary features (generalization is carried out on an essential basis) and the necessary connections between objects and phenomena of nature and society).

The probability of conclusions of scientific induction depends not so much on the number of subjects considered, but on the correctness of the principles of selection, on how accurately the factors influencing the presence and change of the trait under study are taken into account, how scientific the induction is:

Scientific induction is characterized by the search for causal relationships between phenomena and the desire to discover the essential features of objects that are combined into a class. Scientific induction is called inference, in which a generalization is built by selecting the necessary and eliminating random circumstances.

Scientific induction (incomplete) is divided into:

* Incomplete scientific induction "selective" - (induction on a representative sample) (from the Latin - "I choose") - in it, the conclusion about the attribute belonging to a class of objects is based on the study of samples methodically selected from different parts of this class (subset). This is a special kind of enumerative incomplete induction, which is induction through the selection of facts that exclude random generalization.

* Incomplete scientific induction "through the study of a single representative of a certain class" - (eliminative induction on a typical representative) (from Latin - exclude) - typical representatives are selected for premises, i.e. items that are fundamentally different from one another.
Elimination induction, or Eliminative induction (exclusion of different cases) is a system of inferences in which conclusions about the causes of the phenomena under study are built by detecting supporting circumstances and excluding circumstances that do not satisfy the properties of a causal connection.
This is a conclusion about the belonging of a feature to a class of objects, based on the study of typical samples without taking into account their individual characteristics. It is built not only on the basis of the study of a number of phenomena or objects included in a certain class, but also on the basis of the study of a single representative of the specified class. In this case, when reasoning about the belonging or absence of a certain feature of an object, its individual properties that distinguish it from other objects of the same class should not be used. The cognitive role of eliminative induction is the analysis of causal relationships.
Causal is such a connection between two phenomena, when one of them - the cause - precedes and causes the other - the action.
Modern logic describes five methods for establishing causal relationships:
(1) similarity method,
(2) difference method,
(3) combined method of similarity and difference,
(4) concomitant change method,
(5) residual method.


The method of mathematical induction and transfinite induction uses complete induction for infinite countable and uncountable sets of objects, respectively.
The core of mathematical induction is: dispersion , correlation , regression and variational analysis.

From a formal point of view, the essence of the method of mathematical induction is to get rid of the words "and so on ad infinitum."
Deduction often includes the so-called mathematical induction, which is widely used in mathematics.
The conclusion of mathematical induction is composed of two premises and a conclusion.
The first of the premises says that the property under consideration is inherent in the first object of the series under consideration.
The second premise states that if an arbitrary object of a given series has this property, then the object immediately following it also has it.
The conclusion states that the property is inherent in each item in the series.
This type of induction is not yet used in TRIZ.

Scheme of the classical representation of the connection between theory, empiricism, induction and deduction.
Figure. 8. Scheme of the classical representation of the connection between theory, empiricism, induction and deduction. (When refuting inductive conclusions, the researcher returns again to empiricism, to experiments.).

Table 3. INDUCTIVE “TOOLS” and METHODS in TRIZ.
INDUCTION 'TOOLS' and METHODS in TRIZ.

Table 4. Human activity that activates creative, figurative (eidetic) thinking.
Human activity that activates creative, imaginative (eidetic) thinking.

In practice, the researcher, considering a complex System, deals with a chain of cause-and-effect relationships, consisting of non-technical and technical “elementary” systems (See Fig. 9).
In order to optimize a complex System, the researcher consistently analyzes each link in its chain (each “elementary” System) and finds “weak links”.
There is a contradiction (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) in them, which must be circumvented or eliminated by means of TRIZ.

 A chain of cause-and-effect relationships, consisting of 2 non-technical (simplified) and 7 technical 'elementary' Systems.
Figure. 9. Unidirectional, non-branching chain of cause-and-effect relationships, consisting of 2 non-technical (simplified) and 7 technical “elementary” Systems.

Further, in such an “elementary” System or its environment, he is looking for Object 2 (an “elementary” System 2 is being built), on which the influence of the Subject has a negative effect (Object 1 with a positive effect is already known in the “elementary” System 1).
After that, a “root” contradiction (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) is formulated between the two results in “elementary” Systems 1 and 2 (hereinafter, the ARIZ solution).
Separately, deductive analytical methods and “tools” indicated in Table 2 can be used.

For example, in the FA method, the insufficiency of performing a function (impact) in the “elementary” System can be attributed to the conditional “UNWANTED EFFECT” (negative), which is used in ARIZ.
And it is eliminated by searching for a suitable resource inside and outside the “elementary” System, or by its curtailment - the transfer of this function (impact) to another “elementary” System that is part of the complex System under consideration.

Fully connected model of a complex system, consisting of 'non-technical' and 'technical' 8 parts.
Figure. 10. A fully connected model of a complex system, consisting of "non-technical" and "technical" 8 parts as an example.
Parts are marked with colored circles with outgoing (impact by some property (parameter) of the Subject) red arrows and incoming blue arrows (similar properties (parameters) of the Object receive the impact of the Subject and change their value).

Each part of a complex system can both have an impact on other parts, and receive influence from other parts of the system (through parameters of the same type - elements of the "elementary system"). A complex system with its parts is always connected with the environment through some kind of interaction.

The red color indicates the set of the first elements (Subject parameters) of the "elementary system" that act as the influencing Subject, and the blue color indicates the set of second elements (the Object parameters of the same type as the Subject's parameters) of the "elementary system" that play the role of the Object receiving the impact, these elements correspond to different parts complex system and constitute the cause-and-effect relationship of the elements of the "elementary" system.

From the set of "elementary" systems that correspond to some current scientific paradigms, a complex system is built.
The red lines indicate the set of mutually influencing cause-and-effect relationships in a complex system (this is a set of "elementary" systems).
Any complex system is located in the real world and is connected with the environment by cause-and-effect relationships. The incoming and outgoing arrows of each part of a complex system display the interaction of parts of a complex system with the environment and other complex systems.

A researcher who aims to improve the functioning of a complex system needs to analyze all the "links" of the chain of mutually influencing cause-and-effect relationships in a complex system and find "weak" "links" ("elementary systems" that have a negative impact on the functioning of a complex system or its environment).
And they are "elementary" systems that can have:
- insufficiency of functioning, low parameters of functioning, low competitiveness;
- low time between failures (poor fault tolerance);
- subject to rapid destruction;
- subject to parameters going beyond the established technical or other requirements;
- energy inefficient;
- produce a lot of toxic waste;
- adversely affect the performance of other related "elementary" systems;
- have a high cost;
- do not meet aesthetic and ergonomic requirements;
- not economical;
- technological complexity of manufacturing is unacceptable;
- the complexity of operation is unacceptable;
- the complexity of the repair is unacceptable;
- the complexity of storage is unacceptable;
- short service life (resource);
- short shelf life;
- difficulty of transportation;
- low level of sales;
- ineffective work of the staff;
- quick fatigue of the staff;
- the requirements for labor safety are not observed;
- redundancy of personnel;
- etc.).

As a result, the functioning of "weak" links worsens the efficiency of the entire complex system.


"MATCEM+": The impact of any Subject (any part of a complex system can play its role) on
An object (any part of a complex system can also play its role) can be the following
(with increasing or decreasing parameters, constant or alternating, in accordance with accepted scientific paradigms):

● Mechanical (forces, pressures, and, also, there is a dependence of influences on spatial geometry);
● Acoustic (infrasound (low frequency vibrations), sound, ultrasound, hypersound);
● Thermal (heat transfer, convection);
● Chemical (chemical reactions);
● Electric field;
● Magnetic field;
● Electro - magnetic oscillations (quantum) (radio waves, microwaves, infrared radiation, visible light, ultraviolet radiation, x-rays, gamma rays);
● Gravity (including gravitational waves);
● Strong nuclear interactions (binding of nucleons in atomic nuclei);
● Weak interactions (processes of beta decay of atomic nuclei and weak decays of elementary particles);
● Informational (based on "material carrier");
● Biological (based on "biological carriers"- objects of biological origin (flora, fauna)).

Note 1: The information impact of the Subject on the Object, in accordance with accepted scientific paradigms, must have some kind of "material carriers".
To store, transmit, read various information, various states of "material carriers" (which are characterized by certain parameters) can:

● Elementary particles that make up matter (quarks, leptons);
● More complex compound structures (hadrons, atoms, molecules);
● Substances (in chemistry it is customary to divide into individual substances (simple and complex), organized into atoms, molecules, ions and radicals, and their mixtures);
● Interaction carriers (bosons);
● Interactions (strong, weak, electromagnetic, gravitational, interaction of particles with the Higgs field (Higgs boson));
● Sound vibrations (elementary portions of sound energy = quanta of coordinated vibrational motion of atoms of the crystal lattice of a solid body = quanta of elastic vibrations of the medium = quasiparticles = phonons), modulated in frequency, amplitude, phase (infrasound (low-frequency vibrations), sound, ultrasound, hypersound (Frequency 10 to the 9th power of Hz, hypersound is often presented as a stream of quasiparticles - "phonons");
● Electromagnetic oscillations (elementary portions of electromagnetic energy radiation = quanta), modulated in frequency, amplitude, phase (radio waves, microwaves, infrared radiation, visible light, ultraviolet radiation, x-rays, gamma rays);
● Gravitational waves (discovered by the LIGO and VIRGO collaborations in 2016) (in the theory of loop quantum gravity, gravitons are quanta of space-time displacements. Due to the extreme weakness of gravitational interactions, experimental confirmation of the existence of a graviton is currently not possible);
● The description of complex quantum systems with interaction (solids and quantum liquids) is simplified with the introduction of such quasiparticles as: Phonons, Magnetic "quasi-monopoles", Excitons, Wannier-Mott exciton, Frenkel exciton, Trions, Plasmons, Dropletons, Polaritons, Polarons, Magnons , Rotons, Impurities, Defectons, Electron as a quasiparticle, Hole, Cooper pair, Birotons, Biexcitons, Orbitons, Phazons, Fluctuons, Holons, Spinons, Focusons.

Note 2: Biological effects of a Subject on an Object in accordance with accepted scientific paradigms should have at least one element or at most two elements of biological origin in the "elementary" system (flora, fauna).

Note 3: Parameters (Objects) of various types of parts of the NOT Technical System (NTS), which can be influenced by parameters (Subjects) of other parts of the NTS, when their values are significant. (For example: person or community in the range [0 ... 1]):
● generous / greedy;
● honest/dishonest;
● joyful/sad;
● happy/unhappy;
● full/thin;
● young/old;
● healthy / sick;
● rich/poor;
● professional/student;
● educated/illiterate;
● sociable/lonely;
● etc.

    3.3. Adduction - FUTURE LOGIC (bringing, attracting, attaching, attachment, designation when deduction is attached (connected) to induction);

In TRIZ, creative, heuristic, "tools" and methods with incomplete induction can be used inside deductive, algorithmic methods, for example:
in some steps of ARIZ or within some stages of the analysis of the structure and processes in the system under consideration.
The creator of TRIZ, H.S. Altshuller sought to transform (find common features, generalize, classify), as far as possible, heuristic (inductive, "suggestive") methods of thinking into algorithmic (deductive, "according to the algorithm", "according to instructions") to make the search for new solutions more accessible, objective, logically justified, carried out in the shortest possible time, by any interested researcher of the problem.

Inference based on incomplete INDUCTION leads to PROBABILISTIC CONCLUSION.
And inference based on full INDUCTION leads to DEDUCTION (forms a pattern), and unambiguously determines the algorithms that allow you to programmatically simulate the methods and “Tools” of TRIZ.

    3.4. Traductive reasoning, (moving, analogia (other-Greek. analogia - correspondence, similarity)), from the singular to the singular, from the particular to the particular, from the general to the general. Traductive reasoning is an analogy. ('Something' should be like some kind of analog)).

According to the nature of the premises and the conclusion, traduction can be of three types:
• Conclusion from single to single;
• Conclusion from particular to particular;
• Conclusion from general to general.

   In TRIZ, to resolve the contradiction (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) that arises between the results of the impact of a common Subject on 2 Objects in 2 "Elementary Systems", traductive tools and methods are used (analogies from other areas of science, technology, knowledge), which are generalized in 40+10 techniques for resolving contradictions (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) and some individual "tools" and methods of TRIZ.

    3.5. Abduction, Abductive reasoning, (syllogism, a kind of reductive inference, withdrawal, a class of plausible reasoning, search and justification, explanatory hypotheses or the study of facts and the construction of a hypothesis explaining them (assumes that 'something' can be));

   In the history of logic, the idea of abduction in the form of apagogy (proof by contradiction, reduction to absurdity, detection of contradiction) goes back to Aristotle.
   In modern times, abduction was first considered by the founder of pragmatism and semiotics Charles Sanders Peirce (1839 - 1914) , who has been using the term systematically since 1901.
   The term "abduction" was used by Bateson to refer to the third scientific methodology (along with induction and deduction) Gregory Bateson (1904 - 1980). He calls this type of thinking "roundabout", lateral. This is when we think about one thing by thinking about something else, such as through stories, poetry, and similar thought concepts.
   Abduction has a wide field of scientific and applied use, including in artificial intelligence systems.
Georgy Ivanovich Ruzavin (1922–2012) — Soviet specialist in the logic of philosophy and methodology of science, Doctor of Philosophy, professor, academician, writes:
… abduction is used to discover empirical laws that establish the necessary regular connections between observed properties and the relationships of phenomena. …

    3.6. Conventionally, there are three large classes of problems that need to be solved:

    3.6.1. Tasks for optimizing a substance, product, method, process in the mastered areas of human activity (mainly ALGORITHMIC methods are used - "tools" and deductive type TRIZ methods (part of ARIZ, FA, FSA, etc.) .d.), on the scale of H.S. Altshuller - 1, 2, 3 levels - inventions).

    3.6.2. Non-standard, complex, creative tasks - when it is necessary to resolve a contradiction (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) in the system under consideration with the help of a selected (or found, created) substance, product, method, process, structure. TRIZ uses in this case partially deductive methods interspersed with inductive methods, according to the scale of H.S. Altshuller - 1, 2, 3 levels - inventions.

    3.6.3. Non-standard, complex, creative tasks - when in any field of science, when setting up an artificially created experiment or observing a natural phenomenon, reliable facts (results, consequences) appear that do not fit into the accepted scientific paradigm (such a task is called an anomaly task).
When solving an anomaly problem, the cause-and-effect relationship in the model of the "elementary system" of the current scientific paradigm changes and a new scientific paradigm arises (on the scale of H.S. Altshuller - 4, 5 levels - discoveries).

... The research carried out by the scientific community within the framework of the current paradigm is referred to as "normal science".
"Normal science" does not set itself the goal of creating new theories.
The main activity of "normal science" is "solving puzzles", that is, problems that are obviously solvable within the framework of the accepted paradigm.
The period of "normal science" ends when a problem is encountered that does not fit within the current paradigm. Thomas Kuhn calls such a task an "anomaly"...


   4. WAYS AND STRATEGIES FOR SOLVING PROBLEMS.


    4.1. ALGORITMIC - a finite set of precisely specified rules for solving a certain class of problems or a set of instructions describing the order of the executor's actions to solve a specific problem.

The algorithmic way of solving the problem involves the use of a DEDUCTIVE METHOD: when there is a consideration of a PARTICULAR case of WELL-known algorithms.

The algorithmic path is used to solve standard problems of various levels of complexity.

Algorithmic path (DEDUCTIVE METHOD, DEDUCTIONAL LOGIC, from general to particular, rational thinking, ready-made instructions, according to the algorithm) is used in TRIZ in the sequential (formal) execution of ARIZ steps (work according to a given instruction), as well as in the use of a number of TRIZ "tools" related to the assessment, comparison, analysis of the structure and processes in the system under consideration (rational thinking is used).

   4.2. HEURISTIC is an algorithm for solving a problem that includes a practical method that is not guaranteed to be accurate or optimal, but sufficient to solve the problem. Allows you to speed up the solution of the problem in cases where an exact solution cannot be found.

   Heuristic methods are logical techniques and methodological rules of scientific research and inventive creativity that can lead to goals in conditions of incomplete initial information and the absence of a clear program for managing the process of solving the problem.

   HEURISTIC algorithm for solving the problem involves the use of the INDUCTIVE method: this is the process of logical inference based on the transition from PARTICULAR position to GENERAL .

      Professor Lobok.       4.2.1.EDUCATION.

       The INDUCTIVE method is more preferable in the educational process, since it allows you to quickly, with the help of guiding PARTICULAR abstract situations, associations, questions and corrections of the teacher, to rediscover already known (GENERALIZED) knowledge, laws in the sciences, and students to develop creativity and a creative approach to solving problems in various spheres of human activity. Such training is close to the game situation and arouses interest on an emotional level, which allows you to memorize and comprehend new knowledge more deeply.

An example of an inductive, heuristic (empirical, based on the unique acquired experience of each student with repeated use of the trial and error method (TaEM) in solving problems of any direction) can be the methodology of the "PROBABILISTIC TYPE" of Professor Alexander Lobok (definitions are also suitable: random, free, stochastic, ...).
One of the directions of "PROBABILISTIC TYPE" classes in various academic subjects may have approximately the following concept (performed by A. Lobok):

       4.2.1.1. The teacher, for emotional contact with the trainees, constantly changes roles, actively gesticulating, moves: friend, servant, dictator, assistant, sharing the joy of the success of the trainee - but not praising him, empathizing, leading the "show" (finding a solution to the problem) - announcing simple rules of the next task, entertainer – delaying the beginning of the "show" (the beginning of solving the problem) for intrigue, asking leading questions, developing further thought - starting from the learner's answer with derivative questions, etc.
       4.2.1.2. In each task on any academic subject, simple rules of the "game" are announced and the goal (intermediate) to be achieved (the final goal for the trainees remains unknown). The teacher does not give grades.
       4.2.1.3. Multiple guessing, counting, self-checking, errors - words, letters, numbers, syntax signs, shapes, objects, mathematical actions, etc. are allowed both by the trainees and the teacher.
       4.2.1.4. There may be a competition for the duration of the task or the assignment of points by the trainees for each correctly found word, letter, number, syntax sign, figure, object, mathematical action, etc. But this is not necessary.
       4.2.1.5. When all solutions are found, then, several times, a part of the information is arbitrarily deleted or distorted. The trainees themselves, from memory, restore distorted or lost information.
       4.2.1.6. As a result, the true, FINAL, undeclared GOAL of the exercise "manifests" - when the trainees, repeatedly trying by trial and error to find the right properties, parameters, shapes, signs for solving the task:
       4.2.1.6.1. Randomly, deeply and for a long time, remember all the information provided.
       4.2.1.6.2. Randomly establish semantic (semantic) connections between the constituent elements of the presented information (knowledge).
       4.2.1.6.3. Gain confidence that in order to find the right solutions, a stage of sorting and analyzing options, more often erroneous, is necessary. I.e., "they learn from their own and others' mistakes." There is confidence that repeatedly making mistakes and correcting the decision to achieve the goal is a normal process.









      A cup of diagrams of neural network architectures.       4.2.2. NEURAL NETWORKS.

Basically a complete diagram of neural network architectures.
Figure. 11. Basically a complete diagram of neural network architectures ( https://www.asimovinstitute.org/neural-network-zoo/ ).

      4.2.2.1. A heuristic strategy is to solve a problem based on the multiple movement of information (signal) through the multilayer structure of an artificial or biological neural network with a given (or flexible) architecture of feedback between network elements, for the purpose of technical training.
The training consists in finding the coefficients of connections between neurons ("connection weights"). During the learning process, the neural network is able to identify complex dependencies between input and output data, as well as perform generalization.
This method is also called "Experimental" or "Trial and Error" (with correction of the "connection weights" according to the calculated objective function (error minimization - gradual elimination of CONTRADICTION (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) between the values of 2 parameters), in each iteration cycle).

   4.2.2.2. The first stage of the neural network functioning is training, the INDUCTION METHOD is used.
INDUCTIVE method (guidance) - from the particular to the general or generalization, it reveals the relationship between different data (parameters). Neural network training consists in finding optimal values for all weight coefficients w (methods can be: training "with a teacher", training "without a teacher", training with reinforcement (reinforcement learning)).

Training can also be performed by three methods: stochastic method (stochastic), batch method (batch) and mini-batch method (mini-batch).

From the point of view of mathematics, neural network training is a multiparametric problem of nonlinear optimization.

A neural network in the process of tuning (training) to solve a specific problem is considered as a multidimensional nonlinear system that, in an iterative mode, purposefully searches for the optimum of some functional that quantifies the quality of the solution of the task.

There are several methods of teaching NS, the most interesting are three:

   4.2.2.2.1. The Backpropagation method.

   4.2.2.2.2. Resilient propagation or Rprop.

   4.2.2.2.3. Genetic Algorithm.

The main and most common neural network architecture, which revolutionized the teaching of the network "without a teacher" (clustering, self-learning), and also allowed the transition from academic interest to commercial use, is the back propagation network (the method uses a gradient descent algorithm) - a powerful tool for finding patterns, forecasting, qualitative analysis...

Gradient descent is a way of finding the local minimum or maximum of a function by moving along a gradient.

They got this name – back propagation networks because of the training algorithm used, in which the error propagates from the output layer to the input, i.e. in the direction opposite to the direction of signal propagation during normal network operation.

The neural network of back propagation consists of several layers of neurons, and each neuron of layer i is connected to each neuron of layer i+1, i.e. we are talking about a fully connected neural network.

In general, the task of training a neural network boils down to finding some kind of functional dependence Y=F(X), where X is the input and Y is the output vectors. Such a problem, with a limited set of input data, has an infinite set of solutions.

To limit the search space in the neural network training mode, the task of minimizing the objective function of the neural network error is set, which is found by the least squares method.


   4.2.2.3. The second stage of the functioning of the neural network is working, uses the METHOD of DEDUCTION.
DEDUCTIVE method (deduction) - from the general to the particular, it restores the original data set (signal, image) for part of the information from noisy or damaged input data ((auto)associative memory). This is a direct work of the neural network with the initial data on the search for patterns, forecasting, qualitative analysis...(or - promotion and selective change of signal parameters ("filtering"), according to an already configured and verified set of "weights" of neural connections (parallel use of multiple algorithms, "instructions"), in order to find patterns, ...).

From the point of view of the development of computing and programming, a neural network is a way to solve the problem of effective parallelism.

      4.2.2.4. Areas of application of artificially created neural networks in artificial intelligence systems:

   1. Pattern Recognition (objects):
   4.2.2.4.1.1. visual - images (movable/stationary), textual, lexical, semantic (semantic);
   4.2.2.4.1.2. acoustic - conversational, musical, lexical, semantic (semantic);
   4.2.2.4.1.3. taste;
   4.2.2.4.1.4. olfactory;
   4.2.2.4.1.5. tactile - feeling of pain, temperature;
   4.2.2.4.1.6. sense of balance and position in space, acceleration, feeling of weight (analog-vestibular apparatus).
   4.2.2.4.2. Classifications — distribution of data by parameters.
   4.2.2.4.3. Decision-making and management.
   4.2.2.4.4. Clustering is the splitting of a set of input signals into classes, while neither the number nor the attributes of the classes are known in advance.
   4.2.2.4.5. Forecasting - the ability to generalize and identify hidden dependencies between input and output data.
   4.2.2.4.6. Approximations are any continuous function with some predetermined accuracy.
   4.2.2.4.7. Data compression and associative memory - identifying relationships between different parameters makes it possible to present data more compactly if the data are closely related.
   4.2.2.4.8. The reverse process is the restoration of the original data set in terms of information - called (auto) associative memory. Associative memory also allows you to restore the original signal/image from noisy/corrupted input data.
   4.2.2.4.9. Data analysis.
   4.2.2.4.10. Solutions of optimization problems.
   4.2.2.4.11. Finding patterns in large amounts of data.
   4.2.2.4.12. others...

    4.2.2.5. NOTE: Artificially created neural networks do not belong to the philosophical concept:
"Consciousness".
The greatest mysteries: What is consciousness? (RU)
Quantum processes have an impact on consciousness. (RU)
What is the brain? A soul, a computer, or something more? (RU)
Scientists have discovered a key difference between the human brain and the animal brain. (RU)
People with enhanced intelligence can be more effective And. (RU)
The strange connection between the human mind and quantum physics. (RU)
What does quantum theory actually say about reality? (RU)
Neurons responsible for consciousness have been discovered. (RU)
SCIENTISTS CLAIM NEW METHOD CAN MEASURE CONSCIOUSNESS.
Neuropsychoanalysis: what it is and how it can change your life. (RU)
How the brain develops: a new way to shed light on cognition.
Anatomical connectivity influences both intra- and inter-brain synchronizations.
Social Neuro AI: Social Interaction as the "dark matter" of AI.






























   Heinrich Alshuller.    4.2.3. TRIZ (Teoría de la solución de problemas inventivos).
   The heuristic strategy is also part of the problem solving steps, based on the TRIZ methodology - first the problem is modeled (transferred to the level of an abstract model) and then templates are applied to solve it.

An abstract model of a complex system is analyzed: it is divided into separate functional parts, which have different types of cause-and-effect relationships between themselves, and form "elementary systems" (technical and non-technical) in pairs:

   4.2.3.1. Is revealed:
* A subject or Process that directly affects 2 Objects (or 2 Processes, or 2 parts of them) that receive the impact;
* Useful impact (useful function) on the 1st Object (or the 1st Process, or their 1st part);
* Undesirable impact (undesirable function) on the 2nd Object (or the 2nd Process, or their 2nd part);
* Operational areas of influence are determined;
* Models of two "elementary systems" are built;
* The operational time of exposure is determined.

   4.2.3.2. A contradiction (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) is formed between the Consequences in two "elementary systems" and a hypothetical Ideal Final Result (IFR) is formed (in practice, the IFR is not fully achieved).
It is determined which property (parameter) an unknown X-element (substance or method ("modifier" of the properties of the influencing Subject (or Process)) should have.

   4.2.3.3. "Templates" are used to solve the problem model:

   4.2.3.3.1. "Technical methods" - 40 basic and 10 additional;
   4.2.3.3.2. "Standards" - 76 basic;
   4.2.3.3.3. Effects - technological, physical, chemical, biological, mathematical (geometric);
   4.2.3.3.4. Resources - internal, external, above system, functional, their derivatives and variations;
   4.2.3.3.5.1. "Tools" and TRIZ methods that activate creative, imaginative (eidetic) thinking (INDUCTIVE METHODS):
   MLP - Modeling Tool With Little People;
   SFA - Su-field analysis and its analogues;
   STC - Operator Size Time Cost;
   SO - System operator;
   MSB - Method step back from IFR;
   MFO - Method of focal objects (and processes, events);
   MAU - Method to admit the unacceptable ;
   MGF - Method "Goldfish";
   MSB - The "Snowball" method (the opposite of the MGF);
   MRC - Method of "Robinson Crusoe",;
   RIS - Restoration of an inventive technique method or situation;
    … .
The solutions obtained by INDUCTION METHODS are of a PROBABILISTIC CHARACTER, and largely depend on the level of the researcher's work with mental IMAGE representations ("fantasy").


Methods of mathematical logic that are PROBABILISTIC (when analyzing non-technical "elementary systems") in nature are discussed in:
fuzzy logic;
the theory of soft computing;
the theory of computing with words and perceptions).

   4.2.3.3.5.2. Human activity that activates creative, imaginative (eidetic) thinking (INDUCTIVE METHODS):
   - writing and reading literary works (prose and poetry);
   - learning foreign languages;
   - composing and listening to some musical works, roles-reincarnations in theatrical productions;
   - creation and perception of works of fine art, sculpture, decorative and applied art, industrial design, ...;
   - physical activities related to the development and execution of complex biomechanical movements (choreography, ballet, dance, some sports, ...);
   - creative development of technical and scientific plan;
   - solving some puzzles using operations with visual images that require concentration and attention;
   - games of chess, checkers, backgammon, poker, ...;
   - lucid dreaming technique, some actions in ritual religious practices, Eastern meditation and eidetics practices, ...
   … .
   4.2.3.3.5.3. "Tools" and TRIZ methods that activate and determine directions for thinking "according to instructions, according to an algorithm" of a rational type (DEDUCTIVE METHODS):
   ARIZ - sequentially, formal execution of part of the actions in ARIZ steps (work according to a given instruction, algorithm);
   FOS-IFOS - Functionally oriented information search and inverse (reverse);
   AHM - is a 'Harmful system'. Analysis of the 'harmful machine';
   DA - Diversion analysis;
   FA - FUNCTIONAL ANALYSIS OF TECHNICAL SYSTEMS;
   SA - Flow Efficiency analysis. Streaming analysis;
   FCA - Functional Cost Analysis;
   MDMS - Method of decimal matrix search ;
   - solving some logical and mathematical puzzles;
   … .
The solutions obtained by DEDUCTION METHODS are DETERMINISTIC (certain, definition of cause and effect relationships) CHARACTER, and largely depend on the rational thinking of the researcher.



   4.2.3.3.6. An estimated comparison of the variants of the solutions found is made for the maximum approximation of their parameters with the parameter of the X-element (modifier), and then the optimal option is selected.


At various stages of solving the problem and using 'tools' TRIZ, methods can also be applied, which are various forms of managing ideas (concepts): traduction, abduction, induction, adduction, deduction.

After that, from a few units to dozens of options for solving the problem appear, which is hundreds and thousands of times less in number and time, when compared with the method of enumerating options.

The purpose of solving the problem, according to the TRIZ methodology, is to find (SUITABLE or UNKNOWN) AN OBJECT, PROCESS, or METHOD whose parameters (data) are as close as possible to the parameters (data) hypothetically formulated in the "Ideal Final Result" (IFR) for the selected task.
Further, from a finite set of solutions found, one optimal option is selected (the task of OPTIMIZING the solution), and the criteria for its selection can be:

      - satisfaction of the list of requirements, conditions, goals, tasks, resource constraints set by the customer in the terms of reference (or not the terms of reference);
      - do not go beyond the designated budget;
      - do not go beyond the existing production technologies;
      - do not go beyond the existing physical, chemical, environmental, public, legal, etc. laws, restrictions;
      - do not go beyond the required execution time;
      - other restrictions.

   4.2.3.3.7. Note (from Konstantin Kulikov): there is a finite set of "Ideal Final Result" (IFR) for a specific task, which is defined and equal to a finite set of requirements (or restrictions) of the customer, consumer, physical laws, legal laws, environmental, industrial and other standards, public requests, time frames, budget frames, etc. ("stakeholders")
Each such requirement corresponds to its own "Ideal Final Result" (IFR), which must be formulated and its solution found.
Some of the solutions obtained may be in conflict with each other and these contradictions (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) also need to be eliminated.
In the real world, the degree of ideality of the solution of the problem depends on the achievement by the "stakeholders" of a compromise on the requirements put forward by them to the system under consideration.

The analogy of the goals of solving TRIZ problems with one of the classes of tasks that can be solved by artificially created neural networks in artificial intelligence systems is viewed -
This is the restoration of the original data set (signal, image) in terms of information (from noisy or corrupted input data).
Such a task can be described as a reverse process to identify the relationships between different parameters - (auto)associative memory.


     It is possible to notice some analogies in the ongoing processes for both heuristic strategies - this is the TASK OF MINIMIZING the ERROR of the objective function:

   4.2.3.4. To limit the search space in the neural network training mode,
     The TASK OF MINIMIZING THE ERROR OF the objective function of the neural network is set.
     The learning error for the constructed neural network is calculated by comparing the output and TARGET (DESIRED) VALUES. The error function is formed from the differences obtained.
     The error function is an objective function that requires minimization in the process of controlled learning of a neural network.
     Using the error function, you can evaluate the quality of the neural network during training. For example, the sum of squared errors is often used.

   4.2.3.5. Today neural networks confidently solve the tasks of restoring the original data set in:

     4.2.3.5.1. fine arts (digital restoration of works and creation of works in the style of artists who no longer exist);
     4.2.3.5.2. music (digital restoration and creation of works in the style of musicians who no longer exist);
     4.2.3.5.3. literature (restoration of lost fragments of text, writing works in the style of a certain author on a given topic);
     4.2.3.5.4. film industries, old movies (digital restoration);
     4.2.3.5.5. film industries, old black and white movies (digital addition of colors);
     4.2.3.5.6. improving digital recording and playback of photos, videos and audio, getting rid of interference, on various devices, in real time;
     4.2.3.5.7. astronomy (data improvement, clearing of interference received by various types of telescopes);
     4.2.3.5.8. physics (data improvement, cleaning from interference received by various types of detectors);
     4.2.3.5.9. others

   4.2.3.6. Some analogies of processes in neural networks with the processes occurring in the abstract TRIZ model:

     4.2.3.6.1. As SUBJECTS AND OBJECTS in the "technical" (or "non-technical") system, can act: substances, processes, methods, physical fields, information, person, community.
     4.2.3.6.2. PARAMETER is a property or indicator of an object or system that can be measured.
       result of a measurement system parameter is a number or parameter value, and the system itself can be viewed as a set of parameters that the researcher felt it necessary measure for modeling its behavior.
       Parameter — value, the value of which serve to distinguish elements of a set together.
      Parameters can display properties: mathematical, geometric, physical, chemical, informational, socio-psychological qualities of an individual or community, ...

       Parameters can have values of different types (classes): absolute, specific (quantitative ratio), relative (%), vector (gradient), logical (Boolean set), ... (when calculating the OBJECTIVE FUNCTION, parameters having the same type of values should participate).

       A KEY PARAMETER of the SUBJECT 1 acts with the aim of obtaining the DESIRED ACTION (useful functions) in the SETTING of OBJECT 1, but produces UNDESIRABLE EFFECTS (harmful function) OPTION of the OBJECT 2.
      Hypothetically changing (MODIFYING) the state of SUBJECT 1 to the opposite (anti-) state,
INVERT THE KEY PARAMETER OF THE MODIFIED STATE OF SUBJECT 1.
As a result, the UNDESIRABLE ACTION (harmful function) changes to the DESIRED ACTION (useful (or neutral) function) affecting the PARAMETER OF OBJECT 2.

       For quick search of information on a suitable
THE INVERTED KEY PARAMETER OF THE MODIFIED STATE OF THE SUBJECT 1 (affecting THE OBJECT 2) according to the formulated IFR to resolve the contradiction (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM),
it is necessary to have access to databases on PARAMETERS (mathematical, geometric, physical, chemical, informational, ...) that display the properties (PARAMETERS) of substances, processes, methods, physical fields, information, socio-psychological qualities of an individual or community.

And, also, to databases for assessing changes in various types of PARAMETERS, when they are affected by problem solving techniques, problem solving standards, Technological effects, Physical effects, Chemical effects, Biological effects, Mathematical (Geometric) effects, Su-Field Resources (SFR) .
       (For example: The "crushing" technique - what will happen to the physical quantities of the Subject given in the problem, whether and how: mass, volume, area, length, degrees of freedom for elements, angles, ratios, temperature, time, electrical conductivity, dielectric parameters, electric permeability, electric capacity, diamagnetic parameters, luminous intensity, polarization, electrical conductivity, electrical resistance, voltage, current, energy, power, pressure, illumination, electrical potential, etc.).

     4.2.3.6.3. In the considered "technical" system, a NEUTRAL or DESIRED ACTION for OBJECT 2 is obtained from a hypothetical inversion of an UNDESIRABLE ACTION.
     4.2.3.6.4. The requirements for a new desired TARGET PARAMETER for the MODIFIED STATE of SUBJECT 1 acting on OBJECT 2 are formulated in the ICR.

     4.2.3.6.5. IN TRIZ, the TASK IS TO MINIMIZE THE ERROR
    when approaching (finding the minimum discrepancy) between
    INVERTED KEY PARAMETER (real) and
       TARGET PARAMETER (desired)
   MODIFIED STATE OF SUBJECT 1.
     4.2.3.6.6. An error function is formed from the resulting difference – the TARGET FUNCTION.

      4.2.3.6.6.1. Now it is possible to analyze how the INVERTED KEY PARAMETER of the MODIFIED STATE OF SUBJECT 1 will change when using each technical method resolve the contradiction (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM).
The choice of the best technical method of contradiction (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) resolution for this task depends on how the OBJECTIVE FUNCTION will change (the TASK is to MINIMIZE the ERROR of the objective function, i.e., its maximum approximation to zero). The list of technical method: 40 basic and 10 additional (by H.S. Altshuller).
The Decision table is a tabular form of representation in the logic of a Production Rules multitude.
The table contains a set of action algorithms of the form:
      SO that the consequence of the selected specific condition (parcel) is one of the specified results (Production),
      It is necessary to make a decision, which consists in moving to a certain action.
The table achieves a higher degree of formalization and visibility of the decision-making process than when using many separate algorithms.
Decision tables have been used since the 1960s in various fields, for example, in tasks of automating the design of technological processes.





H.S. Altshuller, on the basis of data obtained from the practice of solving inventive problems, compiled a table for the selection of technical contradictions (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM), which is one of the forms (Inverse form or anti-actions on Production Rules) of a Decision table or a visual representation in logic of a Production Rules multitude.
      In the table, in the left column, the selection conditions located here are selected vertically: what needs to be changed (This is an area in logic - a conditions (parcels) multitude).
      In the table, in the upper row, the possible responses of the system to changing conditions are located horizontally: what worsens when conditions change (This is an area in logic - a Production Rules multitude).
      In cells, at the intersections of vertical columns and horizontal lines, information is displayed on the most probable possibility of applying in a given situation the techniques indicated in the cell for solving inventive problems (This is the area of action in logic - Conclusion (decision), which in the given inverse form of the Decision Table are anti-actions, that change the Production Rules to the opposite or neutral).
The inverse form of the Decision table (according to H.S. Altshuller) contains a set of action algorithms of the form:
      SO that the consequence of the selected specific condition (parcel) is not of the specified result (Production),
      It is necessary to make a decision, which consists in moving to a certain anti-action.




Note: H.S. Altshuller at one time analyzer about 40 thousand copyright certificates to generalize and develop 40 basic techniques methods for solving inventive tasks.
      Today, the number of patents in the world is approaching 20 million units, and now it is possible to analyze, generalize, classify these millions of patents with the help of artificially created neural networks in order to develop even more techniques methods for solving inventive tasks.
There may be hundreds or thousands of them.
The same opportunities have opened up for the analysis of scientific discoveries and articles.
       It is also possible to apply an alternative linguistic approach to determining the possible number of TECHNIQUES for resolving contradictions (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) based on the description of all possible actions.
The verb is an independent part of the speech of the English language, which describes:
action, movement, change, state associated with a change in position in space or time of an object or person.
      In modern English dictionaries there are over 1,050,000 words, about 1/7 or about 15% of all words (150,000) are verbs, but the set of stable verb-forming roots is about 2,000.
      This approach allows us to define and describe about 2000 basic VERBS = ACTIONS = TECHNIQUES for resolving contradictions (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) in the problem under consideration.
      The same linguistic approach can be applied to the transformation of TRIZ “tools” using the inductive method into a deductive method (actions according to an algorithm, according to instructions), i.e. formalize the possible actions and states of the “Subjects” of a particular TRIZ “tool” (describe them with 2000 verb-forming roots of the English language).
      For example, MLP: All possible actions and states of the LP (“Subjects”) can be described by 2000 verb-forming roots of the English language, each specific action and state of the LP determines a specific quality or property of the LP (group of LP) - one of which will be the optimal solution for the problem under consideration.


      4.2.3.6.6.2. Possible classification of methods of action.
      Formalization of inductive TRIZ methods in fuzzy logic (successive enumeration of possible ways of action and evaluation of Consequences - changes in the properties of the Object of an “elementary” non-technical System with each action, and then, from a variety of options, choose the most acceptable actions). These groupings of verbs, distinguished on the basis of a common type of action, are semantic, and partly the word is educational.

Table 5. Group (type, class) of verbs, with the meaning: 'ACTION AND ACTIVITY'.

A group (type, class) of verbs, with the meaning: 'ACTION AND ACTIVITY'.

Table 6. Group (type, class) of verbs, with the meaning: “RELATIONSHIP” (“RELATIONAL”).

Group (type, class) of verbs, with the meaning: “RELATIONSHIP” (“RELATIONAL”).

Table 7. Group (type, class) of verbs, with the meaning: "BEING, STATE, QUALITY".

A group (type, class) of verbs, with the meaning: 'BEING, STATE, QUALITY.'

Table 8. Group (type, class) of verbs, with the meaning: 'IMPACT ON THE WILL OF ANOTHER PERSON.'

Group (type, class) of verbs, with the meaning: 'IMPACT ON THE WILL OF ANOTHER PERSON.'

      4.2.3.6.6.3. The system of standards consists of classes, subclasses and specific standards. It includes 76 standards.
      It is possible to analyze how the INVERTED KEY PARAMETER OF the MODIFIED STATE OF SUBJECT 1 will change when using each standard to resolve the contradiction (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM).
      The choice of the best standard for resolving the contradiction (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) of this problem depends on how the OBJECTIVE FUNCTION will change (the TASK is to MINIMIZE the ERROR of the objective function, i.e., its maximum approximation to zero).




      4.2.3.6.6.4. Technological effects, Physical effects, Chemical effects, Biological effects, Mathematical (Geometric) effects have specific PARAMETERS that can change
THE INVERTED KEY PARAMETER OF THE MODIFIED STATE OF SUBJECT 1 when using each effect to resolve the contradiction (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM).
The choice of the best effect for resolving the contradiction (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) of this problem depends on how the OBJECTIVE FUNCTION will change (the TASK is to MINIMIZE the ERROR of the objective function, i.e. its maximum approximation to zero).










      4.2.3.6.6.5. The next stage in the search for a solution to the task may be the use of internal, external, above system, functional resources.
       "Find a goal, resources will be found." - Mahatma Gandhi (1869-1948), Indian political and public figure, founder of the philosophy of non-violence.

      (Substance-Field resources (SFR, Su-Field Resources) - these are resources and their variations, that can be used in solving problems or developing a system.



These can be: substances, their physico-chemical states and compounds, physical fields, time, space, information methods, identification and use of new functions in existing systems, socio-psychological qualities of an individual or community (for example: "Focus groups" in marketing), (for example, such qualities as: drives, hobbies, addictions, emotional passions, collectivism/loneliness, creation/destruction, kind/evil, generous/greedy, happy/unhappy, joyful/sad, honest/dishonest, high/low, light/heavy, thin/full, young/elderly, healthy/sick, rich/poor, fast/slow, educated/illiterate, etc.)).
When formalizing parameters in fuzzy logic systems, socio-psychological qualities (parameters) of a person or community can be expressed in terms of a relative parameter in the range [0 ... 1], which corresponds to a range from 0 to 100% relative to some reference quality (parameter) of a person or community.







The PARAMETER of a certain Su-Field Resources (SFR) can be in close relationship with the INVERTED KEY PARAMETER OF the MODIFIED STATE OF THE SUBJECT 1 and then it becomes possible to influence it through the SFR PARAMETER. As a result, the INVERTED KEY PARAMETER of the MODIFIED STATE OF SUBJECT 1 changes when using each Su-Field Resources (SFR).
The choice of the best Su-Field Resources (SFR) for resolving the contradiction (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) of this problem depends on how the OBJECTIVE FUNCTION will change (the TASK is to MINIMIZE the ERROR of the objective function, i.e., its maximum approximation to zero).






After solving a non-standard problem by heuristic methods, its further optimization is most often performed by algorithmic methods.

      4.2.3.7.Creative, heuristic, inductive TRIZ "tools" and methods can be used inside deductive, algorithmic methods, for example: in some steps of ARIZ or within some stages of the analysis of the structure and processes in the system under consideration.)
      TRIZ creator - H.S. Altshuller sought to transform (find common features, generalize, classify), as far as possible, heuristic (induction, "guiding") methods of thinking into algorithmic (deductive, "according to the algorithm", "according to instructions") methods of thinking, so that the search for new solutions would be more accessible, logically justified, and carried out for the maximum amount of time short time, by any interested researcher of the problem.
      H.S. Altshuller created procedures for finding the "root" contradiction (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) in the system and eliminating it using algorithms (instructions - deductive methods).
      But, some INDUCTIVE "Tools" and methods TRIZ that activate creative, imaginative (eidetic) thinking have not yet been converted from INDUCTIVE methods to DEDUCTIVE (algorithmic, according to the instructions).
      To solve this problem, non-algorithmic TRIZ "Tools" and methods must be classified (typified) in a certain hierarchy and associated with certain logical and mathematical operators (formalized).
      Then, when bringing these "Tools" and methods to uniquely defined algorithms, it becomes possible to simulate them programmatically.
      4.2.3.7.1. DEDUCTIONAL METHODS (with partial inclusion of INDUCTIVE METHODS) narrow the scope of the search for a solution to certain boundaries, which allows you to quickly optimize the existing system, increase its positive effect and reduce, neutralize or eliminate negative properties (According to the Altshuller scale - 1, 2, 3 quality levels solutions - inventions).
      4.2.3.7.2. INDUCTION METHODS, and the most radical of them is the "Trial and Error Method" (TaEM), with the correction of the intermediate result by the "Error" or the "Experimental Method", expand the boundaries of the search for possible solutions and have been used in science for centuries. These methods usually require large material and time costs, but lead to higher results (According to the Altshuller scale - 4, 5 levels of solution - discovery quality).)

      4.2.3.8. TRIZ can be an alternative to TaEM in science, but not when searching for a solution within the considered outdated complex system (since the task is not to optimize the considered complex system, but to replace part of its "elementary systems" with new ones, and such a transition is necessary already at the initial stage of solving the problem ).
      In such new "elementary systems", the positive effect specified earlier in the requirements for obsolete "elementary systems" should be produced. The negative effect previously identified in obsolete "elementary systems" should be absent or insignificant. Such a transition to new "elementary systems" eliminates the appearance of contradictions (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) formulated in an outdated complex system.
      Thus, during a scientific discovery, obtaining new knowledge requires transferring the consideration of the problem to "supersystems", "subsystems" or "alternative" systems of the same level, relatively obsolete "elementary systems".
       The problem is that there can be many such "supersystems", "subsystems" or "alternative" systems with respect to obsolete "elementary systems", including those that are still unknown, therefore their description and choice is a separate task.
      An analysis of the evolution of systems in accordance with empirical patterns and lines of development, used in TRIZ, and is intended to search for new “elementary” Systems. (See Fig. 12, 13).






      It is traditionally believed that the discovery of a new pattern is an example of inductive thinking, largely due to intuition.
      From the point of view of TRIZ, the Current Scientific Paradigm is a "elementary" System in which "Cause" and "Consequence" have an unambiguously defined relationship, there is no CONTRADICTION (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM).
      A causal relationship is the relationship between the first event (the "Cause") and the second event (the "Consequence"), where the "Consequence" is the direct result of the "Cause".
      The 1st Event in the System ("Cause") is the appearance of the Subject's influence ("Cause") on the Object (if necessary, it can be recorded by the observer).
      The 2nd Event in the System ("Consequence") is a change in the properties of the Object (if necessary, it can be recorded by the observer).
      In the Current Scientific Paradigm, when an 2nd Event in the System occurs, certain, deterministic, already proven by numerous experimental data changes in the properties of the Object ("Consequence", result) are always obtained.
      If an anomalous (false) result ("NOT Consequence") of the functioning of such a System is detected (for example, in case of significant changes in the states of the Subject (which, in turn, may be influenced by the state of the external or internal environment)), then a CONTRADICTION (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) appears in the System between the result of the impact of various states of the Subject on the Object, and the Current Scientific Paradigm is partially or completely false.
      In the appeared anomaly task, it is necessary to search for an aggravated, root CONTRADICTION (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) between two different results of the IMPACT of 2 different states of the Subject on the Object (true / false).
      It is necessary to observe and analyze an abnormal natural phenomenon or experiment (the processes under consideration can be both real and abstract).
      At the same time, objective "Entities" are revealed - these are objects, facts, phenomena, operations, processes, etc.
      Each "Entity" has a number of characteristic properties or features (parameters) for it.
      The influence of parameters on each other is analyzed (Cause-and-Consequence relationships, properties, relationships, both qualitatively and quantitatively, through the construction of mathematical formulas), an abstract model of the process is constructed, modeled (systematization) .
      (Relationships determined with the help of the senses (subjective): "Subject - impact", "To be - earlier", "To be - later" ... Relationships determined using logical conclusions ( objective): "Cause - Consequence", "Purpose - means" ...)
      When the 1st state of the Subject ("Cause") acts on the Object, the true result ("Consequence") appears, already proven earlier in the Current Scientific Paradigm (True = "DESIRED ACTION" ).
      When the 2nd state of the Subject ("Cause") is exposed to the Object, a false result ("NOT Consequence") appears, anomalous for the Current Scientific Paradigm (False = "UNWANTED ACTION") .
      An Ideal Final Result (IFR) is compiled for the anomaly task.
      The goal in IFR is to achieve the absence of CONTRADICTION (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) in the System.
      To achieve this goal, you need to get the true result ("Consequence") - the impact of each of the 2 states of the Subject ("Causes") on the Object, which is uniquely determined by the mathematical relationship between certain parameters Subject and Object within the boundaries of one phase state of the Object.
      (Critical phenomena - characterize the behavior of substances in the vicinity of phase transition points. Phase transition (phase transformation) is a critical phenomenon, which is characterized by an abrupt change in some parameters of the Object. The theory of critical phenomena was first built L.D. Landau and develops further, in physics, for example, critical phenomena are described by methods of quantum field theory.)
      In case of transition of the Object's state through the boundary of the critical phenomenon (when it is exposed to the 2nd state of the Subject ("Cause")), the true result ("Consequence") in another phase state of the Object is described by a different mathematical dependence within the boundaries of this phase state.
      (As applied to substances: not every phase transition is accompanied by a change in the state of aggregation. But any change in the state of aggregation is a phase transition.)
      Note: In some modern physical hypotheses and theories there is still no understanding at the physical level of the Subject ("Causes"), for example, when a physical body has an inertial force, gravity. Also, when describing the model of the world at the quantum level, there is not always an understanding at the physical level of the Subject ("Cause") of a particular phenomenon.
      At the same time, the results ("Consequences") of such phenomena are well studied, described by equations, and are widely used in various devices.
      i.e. in scientific research it can be like this: the Subject (“Cause”) does not have a description at the physical level, but its effect on the Object (result, “Consequence”) is well studied, mathematically described, experimentally reproduced and verified, widely used in various devices.
      To describe the Subject ("Cause") in the system under consideration at the physical level, it is necessary to consider the cause-and-effect relationship at the Supersystem level (in each specific task, there may be one Supersystem or a set of Supersystems located in related hierarchical (subordinate) relationships).
      The Subject ("Cause") of the subordinate System is equivalent to the Supersystem Object. The Subject of the Supersystem (the "Cause" of the Supersystem) acts on the Object of the Supersystem and a uniquely defined result (the "Consequence") of this influence appears - this is a change in the properties of the Object of the Supersystem, which makes it possible to approach its understanding at the physical level.
      Next, you can formulate a hypothesis about a new Paradigm that describes the ongoing process (generalization, synthesis), develop an experiment to confirm the hypothesis and reproducibility of the new Paradigm.
      The result is a new regularity (law) that is valid for this natural phenomenon or experiment (there is a change in the Scientific Paradigm).
      NOTE: In the STRUCTURAL AND FUNCTIONAL ANALYSIS of complex non-technical and technical devices and systems, there are also cause-and-effect relationships. Technical devices, their parts, modules or nodes, consist of many interconnected "elementary" Systems (Analogue: "Elementary" technical System, consists of the same logical elements as any System of the Current Scientific Paradigm, and there is no CONTRADICTION (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM) in them) .
       The logical elements of such a system are the Subject ("Cause") and the Object receiving the impact. In this case, a uniquely defined result (“Consequence”) appears - this is a change in the properties of the Object.
      (The qualities (parameters) of a community of people or an individual also fit into many interconnected "elementary" Systems, but the results of the impact ("Consequences") may have a more variable, probabilistic character, which in some cases are trying to limit the "corridor of opportunities").

      An "elementary" System can be represented as a scheme "Input - Process - Output", or "Subject - Impact - Object" and make a chain of such "elementary" Systems (a set of Causal Relationships), for further analysis (Fig.):
Elementary Systems
Figure. 12. The structure of the scientific revolution (version 1, level 4 of the H.S.A. scale, the transition of the properties of the Object through a critical phenomenon (phase transition point) to a new phase state with a significant change in the state of the Subject): a jump is a transition to the "elementary" System of the NEW SCIENTIFIC PARADIGMA .

       A complex technical System consists of a multitude of "elementary" Systems connected by cause-and-effect relationships.
       Each technical "elementary" System is a private implementation of the CURRENT SCIENTIFIC PARADIGMA, i.e. the SCIENTIFIC PARADIGMA is also represented by the "elementary" System, but in a generalized form.
       The scientific revolution is a transition from the "elementary" System of the OUTDATE CURRENT SCIENTIFIC PARADIGMA to the "elementary" System of the NEW SCIENTIFIC PARADIGMA.
       Example:
       (Version 1) Discovery and description of any phase transitions of substances.
       With a significant change in the state (properties, parameters) of the Cause (Subject), there will be a significant change in the state of the Consequence (Object), while the properties (parameters) of the Consequence (Object) can make a transition through a critical point to a new phase state, and in the "elementary system "There will be a new causal relationship.
       (Version 2) is the transition from the "elementary" System of the OUTDATE CURRENT SCIENTIFIC PARADIGMA to the "elementary" System of the NEW SCIENTIFIC PARADIGMA.
       At the same time, both the Cause (Subject) and the Consequence (Object) are replaced, and a new causal relationship appears between them.
       The main function of the "elementary" System remains the same, but the positive effect produced by the function increases. Example: Transportation of passengers and goods: the function is the same, but the speed and comfort of transportation change. The number of “elementary” systems is increasing, and they are changing, in accordance with new SCIENTIFIC PARADIGMS. (See Fig. 13). At the same time, the Cause (Subject) and Consequence (Object) are replaced, and a new causal relationship appears between them.

Elementary Systems
Figure. 13. The structure of the scientific revolution (version 2, level 5 of the H.S.A. scale, complete replacement of the Subject and Object): a leap - a transition to the "elementary" System of the NEW SCIENTIFIC PARADIGMA.

       A complex technical System consists of many "elementary" Systems connected by cause-and-effect relationships.
       Each technical "elementary" System is a private implementation of the CURRENT SCIENTIFIC PARADIGMA, i.e. the SCIENTIFIC PARADIGMA is also represented by the "elementary" System, but in a generalized form.
       Used in TRIZ, the analysis of the evolution of technical systems (and, accordingly, scientific paradigms) in accordance with empirical laws and lines of development, for greater scientific objectivity, requires a more rigorous definition in the form of mathematical dependencies (formalization, a possible transition to quantitative parameters), and is represented in the form of stepwise transitions of "elementary systems" to more and more perfect cause-and-effect relationships.
       (For example: Moore's empirical law of doubling the number of semiconductors every 2 years (and according to David House of Intel, every 1.5 years) is quantitative.)
       In the scientific method, in the process of observing any natural phenomena or artificially constructed experiments, various facts are recorded. Complex systems are divided into parts ("elementary systems" technical and non-technical).
       In the study of technical "elementary systems", based on the analysis of the facts obtained, the Subject acting on the Object (and a possible change in their states) is identified, an abstract model of the process is created, and a causal relationship is revealed. By methods of incomplete scientific INDUCTION, generalizations are carried out, empirical and, then, mathematical deterministic dependencies are derived.
       In the study of non-technical "elementary systems", logical formalization is carried out by fuzzy logic methods and the results are of high probability.
       There is a tendency in TRIZ to reduce TRIZ "Tools" and methods to uniquely defined deterministic algorithms where possible. Such a need is due to the fact that the solution process should be more objective, unambiguous, scientifically substantiated, excluding the subjective factor of the researcher of the problem and better amenable to software modeling.



      4.2.3.9. And here a natural question arises in relation to Artificial Intelligence (AI) systems created on the basis of neural networks (NN):
what needs to be done so that the NN in the process of solving the problem "goes" beyond the limits of the task in the outdated "elementary system" and creates (designs) a new "elementary system" on other principles of functioning using the resources of the "supersystem", "subsystem" or "alternative" system, relative to the level of the obsolete "elementary system"? (An analogy from thermodynamics - "phase transition" ("phase transformation")).
      Or is this property (“privilege”) inherent only in the NS of natural origin in some scientists-researchers (human intellect)?
      And will this form of "information processing" in AI systems become the moment of the birth of a full-fledged, “strong” intelligence (the hypothesis of a technological singularity, called the “intellectual explosion” by the British mathematician and cosmologist Irving John Good.



      This may be the very moment when AI will be able to put into practice the search (or construction) of unknown (hidden) new "elementary systems" on other principles of functioning using resources of "supersystems", "subsystems" or "alternative" systems, relative to the level of the obsolete "elementary system".
      Perhaps, with such a transition to the new "elementary system", new causal relationships will appear, which may differ from the relationships in the outdated "elementary system".








Note: Can some works of abstract art influence the researcher in "constructing" a new system?
Before the advent of photography, the purpose of creating works of art was to capture various characters, moments of life, history, mythology, religion ... using various expressive forms.
When affordable photography, video, printing, 3D printing appeared, then many functions of art became possible to quickly reproduce in these technologies.
What functions have modern art created by man, and not by technology? What is the purpose of contemporary art?
The following answer suggests itself: machine technologies cannot go beyond the limits set, determined by their design and programs, they can combine them, mix them, distort them in different ways, brighten / darken, filter, connect / separate, repeat, change the scale, etc.
And some artists can go beyond their "everyday rationalism", "program of rational existence", "psychological inertia" imposed by the living environment and the surrounding society in their works of abstract art.

      4.2.3.10. Thus, there is a need to search and describe the hypothetical conditions of existence, properties, features and principles of functioning of such unknown (hidden) "elementary systems" of various levels, relative to the level of the outdated "elementary system".

      4.2.3.10.1. The minimum specified requirements for the properties of the new "elementary system" are defined as:
      - should produce a positive effect (similar to the effect of the obsolete "elementary system");
      - there should be no negative effect (similar to the effect of the outdated "elementary system");

      4.2.3.10.2. Principles of operation suitable for use in the new "elementary system" may be in another area of knowledge and for transfer they can use the method of thinking - traduction (movement, analogy).

      4.2.3.10.3. Principles of operation suitable for use in the new "elementary system" can be generated by hypotheses using the method of thinking - abduction (a cognitive procedure for putting forward hypotheses - from the first premise, which is a conditional statement, and the second premise follows from the conclusion (syllogisms have: 3 rules of terms, 4 rules of premises, 4 figures, 256 modes, 24 correct (reliable) conclusions, 232 incorrect (probabilistic) The semantic verification of the syllogism is carried out using three-dimensional diagrams - Euler circles).

      4.2.3.10.4. Principles of operation suitable for use in a new "elementary system" can be generated by empirical testing of hypotheses put forward or by consideration of hypotheses and measuring the extent to which they agree with the facts. The method of thinking used is induction (guidance, from particular to general, search for common properties, signs, and finally - generalization of experimental data)...

      4.2.3.10.5. In the new “elementary system”, when using a new principle of functioning and establishing a new cause-and-effect relationship, a change of Subject and Object must occur.
      To select a new Subject and Object, it is necessary to use real-field resources (VFR) located inside and around the considered "elementary system".

Table 9. Su-Field Resources (SFR) are divided:

Su-Field Resources (SFR) are divided:

      4.2.3.11. Identification of heuristic potential, through various stages of human thinking, to search and explore the properties of a new system.
      The founder of the research tradition of studying higher psychological functions, Lev Semyonovich Vygotsky (1896-1934) and the creator of The Theory of Cognitive Development, Genetic Epistemology, Operational Theory of Intelligence, Jean William Fritz Piaget ( 1896-1980) , single out "BEFORE CONCEPT" and "CONCEPT" periods of thinking as carriers of the heuristic potential of human thinking.

From left to right: Lev Semyonovich Vygotsky, Jean William Fritz Piaget.
Figure. 14. From left to right: Lev Semyonovich Vygotsky, Jean William Fritz Piaget.

       4.2.3.11.1. The “BEFORE CONCEPTUAL” period has an independent value; PROJECTIVITY or PROBABILITY. The research process is built according to the laws of game improvisation, and the researcher's thinking grid is a PROBABILISTIC grid that forms the “manifestation” of the initial contours of the new system.

Images in consciousness. The
Figure. 15. Images in the mind. The "PRIOR CONCEPT" period has an independent value, it lays the foundations of irrational-creative structures of human consciousness. (etchings by Sergei Balenok , traits on the sheet that create images are perceived as a kind of "projection of weights of neural connections" of the artist).

      4.2.3.11.2. First, undifferentiated thinking (“SYNCRETIC” period) is described. The phenomenon of "SYNCRETISM" consists in the desire to lump together the most diverse elements that do not have an internal connection, bringing them into an undivided, fused image, i.e. to replace the lack of objective connections with an overabundance of subjective connections and to take the connection of impressions and thoughts for the connection of things.
      And in this overabundance of subjective ideas and assumptions lies the heuristic potential that has always distinguished the thinking of those people whom we call outstanding and brilliant. There is no generalization and systematization of the surrounding world at this stage of thinking, pure subjectivism is manifested.

The phenomenon of 'SYNCRETISM' is the tendency to lump together the most diverse and unrelated elements.
Figure. 16. The phenomenon of 'SYNCRETISM' consists in the desire to lump together the most diverse elements that do not have an internal connection, bringing them into an undivided, fused image, those. replace the lack of objective connections with an overabundance of subjective connections and take the connection of impressions and thoughts for the connection of things.

      4.2.3.11.3. "COMPLEXES" - it lays the fundamental foundations for a creative-variative attitude to the object of study).
      At this stage of thinking, there is an attempt to generalize and systematize the world around us based on some objective connections; however, these generalizations each time have individual variability and ambiguity, the ability to subjectively arrange objective connections is formed, which means that thinking does not just follow one or another objective regularity, but also enters into a creative dialogue with these regularities.
      Each element of the "COMPLEX" can be associated with the whole, expressed in the "COMPLEX", and with the individual elements included in its composition, with a variety of connections.
      In "CONCEPT" these connections are basically the relation of the general to the particular and the particular to the particular through the general.

       Notice that:
- the associative complex has a nuclear structure,
- chain-like - diffuse and chain, and
- amorphous - complex-collection. (See Fig. 17).

Configuration of the structure of complexes according to L.S. Vygotsky.
Figure. 17. Structure configuration of complexes according to L.S. Vygotsky.

      4.2.3.11.3.1. "ASSOCIATIVE COMPLEX" - any associative connection with any of the features noticed by the researcher in the object that in the experiment is the core of the future complex. It is possible to build a whole complex around this core, including in it the most diverse elements, united by some identical feature. Any "lateral", "incorrect", random associative connection between the core and the element of the complex turns out to be a sufficient reason for referring the object to the group selected by the researcher and for designating this object with a common family name (type, class).

“ASSOCIATIVE COMPLEX” (“NUCLEAR”). Figure. 18. “ASSOCIATIVE COMPLEX” (“NUCLEAR”).

      4.2.3.11.3.2. "COLLECTION COMPLEX" - various specific objects are combined on the basis of mutual complementation according to any one attribute and form a single whole, consisting of heterogeneous, complementary parts. It is the heterogeneity of the composition, mutual complementation and unification on the basis of the collection that characterizes this stage in the development of thinking. However, the researcher selects them not chaotically and not randomly, but on the basis of their difference and addition to the main feature contained in the sample and taken as the basis for association. The principle of variability and the principle of complementarity are used.

“COLLECTION COMPLEX.”
Figure. 19. "COLLECTION COMPLEX".

      4.2.3.11.3.3. "CHAIN COMPLEX" - is built on the basis of a dynamic, branching chain of associations. For example, a researcher to a sample - an object with a feature (property, parameter) "A" and "B", selects objects with similar features, and then, if the last of the selected objects turns out to be with a feature (property, parameter) "A" without a feature ( property, parameter) "B", the researcher selects other objects with the attribute (property, parameter) "A" and "C", but without the attribute (property, parameter) "B". This again turns out to be sufficient to approach a new attribute (property, parameter) and pick up items further according to the attribute (property, parameter) "C".
      During the formation of a "chain COMPLEX", a transition is made from one feature (property, parameter) to another. Thus, in the "chain COMPLEX" the structural center may be completely absent. Particular concrete elements can enter into a relationship with each other, bypassing the central element or pattern, and therefore may not have anything in common with other elements, but nevertheless belong to one "chain COMPLEX", since they have a common feature with some another element, and this, the other, in turn, is connected with the third, and so on.
      The transition from one structurally organizing center of thinking to another takes place according to a completely random, probabilistic logic, and it is at the point of this probabilistic transition (or in a series of these poorly motivated, probabilistic transitions) that what we call scientific discovery.

“CHAIN COMPLEX.”
Figure. 20. "CHAIN COMPLEX".

      4.2.3.11.3.4. “DIFFUSE COMPLEX” is a sign that associatively combines individual specific elements and “COMPLEXES”, as it were, diffuses, becomes indefinite, spilled, vague, as a result of which a complex is formed that unites, with the help of diffuse, indefinite connections, visually - specific groups of images or objects.
       The researcher, for example, to a given sample - an object with a feature (property, parameter) "A" - selects not only objects with a feature (property, parameter) "A", but also objects with similar features (properties, parameters) "-A +", as they remind him of the features (properties, parameters) "A" of the modified initial object. Further to the features (properties, parameters) "-A+" of the object, derivative features (properties, parameters) "--A++", "---A+++", etc. can adjoin.
      Just as here the form, taken as the main feature, spills and becomes indefinite, different features (properties, parameters) also sometimes merge. But after all, the ability to think in blurry, approximate, fuzzy outlines is the ability that fundamentally distinguishes heuristic thinking from thinking focused on the available forms of knowledge and understanding, and in this way the fundamental unlimited possibilities of expansion and inclusion in the main genus (type, class) can manifest themselves. more and more new, but completely specific objects. The limitless "COMPLEXES" generated by creative people often amaze with the universality of the connections they unite.

“DIFFUSE COMPLEX.”
Figure. 21. "DIFFUSIVE COMPLEX".

      4.2.3.11.3.5. “PSEUDO CONCEPT COMPLEX” – is formed by the researcher whenever he selects a number of objects to the given sample that could would be selected and combined with each other on the basis of some abstract concept.
      For example, a researcher to a given sample - an object with a feature (property, parameter) "A" - selects all the objects in the experimental material with a feature (property, parameter) "A". Such a group could also arise on the basis of abstract thinking (the concept or idea of an object with a sign (property, parameter) "A"). But in fact, as the study shows, the researcher combined objects on the basis of their specific, factual, visual connections, on the basis of simple association. He built only a limited "ASSOCIATION COMPLEX"; he came to the same point, but went in a completely different way.

“PSEUDO CONCEPT COMPLEX.”
Figure. 22. “PSEUDO CONCEPT COMPLEX”.

      4.2.3.11.4. Any theoretical thinking, as scientific studies have shown already in the 20th century, is based on a certain "IMAGERING LINING" - the totality of what could be called "INTELLECTUAL IMAGERY". Any genuine understanding does not begin at all at the “CONCEPTUAL” level, but at the level of intuitive grasp of the “IMAGE OF UNDERSTANDING”.
      and only through “personal figurative structures” ascends to the “essence of the actual concept”. Moreover, although the "IMAGE" does not have the accuracy and clarity of "CONCEPTUAL STRUCTURES", it has a "HUGE POTENTIAL OF HEURISTICITY".
      There is no universal universality of the "CONCEPT" in this "FIGURE LINING", but there is a coiled spring of huge cognitive interest, functioning according to the laws of inaccurate, approximate, vague, incorrect thinking - thinking in "COMPLEXES" .
      At first, thinking is characterized by "COMPLEX" thinking with a predominance of "PSEUDO CONCEPTS" (which corresponds to the boundaries of concrete - operational thinking), and only then do "CONCEPTUAL" structures develop (a stage of formal operations arises) , "thinking in CONCEPTS", while the formation of a new system is completed.

At first, thinking is characterized by 'COMPLEX' thinking with a predominance of 'PSEUDO CONCEPTS' (which corresponds to the boundaries of concrete operational thinking), and only then do 'CONCEPTUAL' structures develop (the stage of formal operations arises), 'thinking in CONCEPTS'.
Figure. 23. First, thinking is characterized by 'COMPLEX' thinking with a predominance of 'PSEUDO CONCEPTS' (which corresponds to the boundaries of concrete - operational thinking), and only then do the actual "CONCEPTUAL" structures develop (the stage of formal operations arises), "thinking in CONCEPTS".

      4.2.3.11.5. Based on the concepts of operational thinking by L. Vygotsky and J. Piaget, it is possible to create a software package that will help the researcher and the neural network to create new “CONCEPTS” in various areas of human activity. (See Figure 24).

Possible structure of successive stages of the software package based on the concepts of operational thinking by L. Vygotsky and J. Piaget.
Figure. 24. Possible structure of successive stages of the software complex based on the concepts of operational thinking by L. Vygotsky and J. Piaget.

      5. "INSIGHT" — sudden conscious finding of a solution to some non-standard problem, which became the result of prolonged unconscious mental activity.

In psychotherapy, insight refers to a person's awareness of the causes of his condition or problem accompanied by insight and catharsis.

The appearance of insight is facilitated by a change in human activity. There are also special technologies, such as business games and the brainstorming method.

Insight is actively used in psychodrama. After solving the problem by the "illumination" method, its further optimization is most often performed by algorithmic methods.

Intuition (late Latin intuitio "contemplation" from the verb intueor "gaze") is the ability, the property of a person to understand, form and penetrate into the meaning of events, situations, objects through insight, insight, simultaneous unconscious conclusion (based on imagination, empathy and previous experience), "flair", insight.


      METHODS

      6. METHODS FOR SOLVING THE PROBLEM.

       

   6.1. 'The Triangle of the Conflict Process' in the TECHNICAL sphere.

Built on the basis of the 'Su-fieldl Analysis' (substance - field analysis is a 'tool' classic ARIZ).

'Su-field' is a model of a minimum operable managed technical System (of the 'Elementary' System)- consisting of at least three parts: two SUBSTANCES (Subject and Object (or Process)) and their interactions - one 'FIELD'.

Any complex technical system can be reduced to the sum of 'Su-fields'.

The term 'FIELD' is a conditional name for the energies (forces, information) of interactions in the system (determines the action of the Subject on the Object in the system), that are present or added:

Mechanical, Acoustic, Thermal, Chemical, Electrical, Magnetic, Electro-Magnetic, Gravitational,
Strong nuclear interactions (binding of nucleons in atomic nuclei), Beta decay (processes of beta decay of atomic nuclei and weak decays of elementary particles), Informational, Biological.




      6.2. In TECHNICAL systems, elements of natural or artificial origin have an unambiguously defined response.

The exception is interactions in quantum mechanics: quantum effects are mainly manifested on microscopic scales and the predictions of quantum mechanics can differ significantly from the predictions of classical mechanics.
Quantum field theory in the form of a Standard Model (with the addition of neutrino masses) is now the only experimentally confirmed theory capable of describing and predicting the behavior of elementary particles at HIGHT energies (that is, at energies significantly EXCEEDING their rest energy.
The uncertainty principle, discovered by Werner Heisenberg in 1927, is one of the cornerstones of physical quantum mechanics: The more accurately one characteristic of a particle is measured, the less accurately the second can be measured (for example: coordinates and momentum, current and voltage, electric and magnetic fields). The uncertainty principle is a consequence of the principle of particle-wave dualism.
The creation of a Unified field theory (Theory of everything), a physical theory that aims at a unified description of all known physical phenomena based on a single primary field, faces the lack of primary concepts in physics - what they are and what they consist of: space, time, matter in space, infinity of space, and the substitution of these primary concepts for abstract "surrogates".



      6.3. The choice of Object 1 (or Process 1) determines the DESIRED ACTION (useful function) that is required to be obtained from the TECHNICAL system according to the conditions of the problem.
Or, in order to determine Object 1 (or Process 1) based on the conditions of the problem, the following question must be asked:
the parameters of which element of the system must be improved according to the conditions of the problem?

Selection of Object 2 (or Process 2), which is exposed to UNWANTED ACTION (harmful function),
complicated by the fact that Object 2 (or Process 2) occupies a 'floating position' and in each new task it can coincide with some other element of the system or have only an indirect connection with the technical system, this is due to the variety of tasks solved in the TECHNICAL area:

► 1. Conflict triangle 1 (Reaction)    Object 2 (or Process 2) = Subject 1. (Reaction).

► 2. Conflict triangle 2 (Conjugate action).    Object 2 (or Process 2) = Object 1 (or Process 1). (Conjugate action).

► 3. Conflict triangle 3 (Conjugate action).    Object 2 (or Process 2) = Part of the system that also contains Object 1 (or Process 1). (Conjugate action).

► 4. Conflict triangle 4 (Conjugate action).    Object 2 (or Process 2) = In a separate system, but which is connected with the system of Object 1 (or Process 1) and Subject 1. (Conjugated action).

► 5. Conflict triangle 5 (Conjugate action).    Object 2 (or Process 2) = Subject 1 acts on itself (complication of the system). (Conjugate action).

► 6. Conflict triangle 6 (Incompatible action).    Object 2 (or Process 2) = Subject 1. (Incompatible action).

► 7a. Conflict triangle 7a (Incompatible action).    Object 2 (or Process 2) = Object 1 (or Process 1). 2 equal actions are required (One action is set, the other is not). (Incomplete action).

► 7b. Conflict triangle 7b (Incompatible action).    Object 2 (or Process 2) = Object 1 (or Process 1). Subject 1 does not work. (Incomplete action).

► 7c. Conflict triangle 7c (Inaction).    Object 2 (or Process 2) = Object 1 (or Process 1). Not specified Subject 1. (Inaction).

► 8a. Conflict triangle 8a ('Silence').    Object 2 (or Process 2) = Object 1 (or Process 1). Not specified Subject 1, not specified Object 1. You need to get information about Subject 1 and Object 1. ('Silence').

► 8b. Conflict triangle 8b (Conjugate action).    Object 2 (or Process 2) = Object 1 (or Process 1). The impact of Subject 1 is not specified. It is necessary to obtain information about the impact of Subject 1. (Conjugate action).

► 9. Conflict triangle 9 (Unregulated action (in particular, redundant)).    Object 2 (or Process 2) = Object 1 (or Process 1). (Unregulated action (in particular, redundant)).
       

   6.4. 'The Karpman Triangle' ('The Triangle of Fate', 'The Triangle of Toxic Relationships') in a NON-TECHNICAL sphere.

      6.4.1.This method is used in PSYCHOLOGY, PSYCHOTHERAPY for the analysis and resolution of CONFLICT situations.
There can be more than a hundred shades of the interdependence of the triangle elements.
The main goal is to go beyond this triangle or the destruction of toxic bonds within the triangle.

This method can be adapted to the CONFLICT interaction of elements included in the humanitarian fields of activity, such as:

sociology, pedagogy, law, economics, competition in business, managerial and other tasks in the organization, diplomacy, culture, storyline of literary works, storyline of films, etc.


















      6.4.2.In the NON-TECHNICAL field of activity, most of the elements of the system are of natural (and sometimes artificial origin),

      at least have a flexible, adaptive program of multivariable response actions to resist Subject 1 ('Aggressor') (for example, Subject 2 ('Rescuer, Peacemaker') opposes, hinders Subject 1 ('Aggressor') with one or another predefined (or programmed) flexible, adaptive, multivariablere sponse actions),

      as a maximum - has a collective or individual will, intelligence, consciousness.
Making a decision on the response is probabilistic, ambiguous and depends on many factors.

      In all higher animals, without exception, the processes of formation of conditioned reflex connections are much more complicated than in the lower representatives of the animal world.
      If the latter really trace the reaction of the organism as a direct function of the stimulus, then in higher animals this reaction is mediated by a complex
structural and functional organization of internal perception mechanisms, although it remains closely related to the input effect.
      Physiologists often observe how, with the continuation of training of an already trained animal, soon, for no apparent reason, individual stimuli of the complex lose the ability to cause a conditioned reflex.
      This means that now the complex stimulus has ceased to be a simple set of individual stimuli for the animal
, but has become a single independent stimulus ("image"), sharply different from each component included in it.
      This happens because temporary connections were formed between the neurons to which the components of the complex stimulus arrive, which led to the creation of a common functional center.
      In a person, such a factor as "attraction" has a great influence on his mental movement and behavior. "Attraction" is one of the central concepts of the theories of psychoanalysis (as part of the so-called theory of drives).
      This is the desire to satisfy an unconscious or poorly realized need and therefore the primary source of any mental movement and behavior.       There are more than 100 methods for converting fuzzy inferences at the linguistic level into computational circuits. Using formulas, a fuzzy production rule can be represented graphically.

6.4.3. Examples of the natural origin of interacting system elements in the NON-TECHNICAL sphere:
Unicellular organisms do not have a nervous system, but some infusoria have an intracellular mesh that performs the function of conducting excitation to other elements of the cell, which allows them to learn how to develop the simplest defensive reaction to an irritant.
Multicellular organisms have a nervous system, which allows them to develop more complex conditioned reflexes to various stimuli (multivariable defensive reactions).
The development of the nervous system (during phylogeny), occurred:
      - from the most primitive form, preserved only in the lower coelenterates (hydra) - diffuse nervous system;
      - through the type of nodal nervous system usually inherent in invertebrates;
      - to the Central nervous system (CNS) in vertebrates, consisting of the spinal cord and brain.

      6.4.4. Examples of the artificial origin of the interacting elements of the system in relation to a person, the community of people, ecology, legislation, etc. in NON-TECHNICAL area:
      6.4.4.1.- analog and digital automatic control systems for complex actuators, complexes and systems, built on various element bases (mechanical, pneumatic, hydraulic, biological, electronic, quantum, hybrid);
      6.4.4.2.- algorithmic type software (procedural or object-oriented execution) with results depending on a set of specified, interdependent and calculated conditions;
      6.4.4.3.- software and architecture for neural networks in artificial intelligence systems...

      6.4.5. Striking examples of artificial intelligence systems that have heuristic, flexible, adaptive programs of multivariable responses are:
      6.4.5.1.- AlphaGo - a go game program that defeated human champions, developed by Google DeepMind in 2015;
      6.4.5.2.- In (backgammon, checkers) chess - Stockfish, Shredder, Fritz, Komodo programs have already far exceeded the level of human champions;
      6.4.5.3.- In 2017, the Libratus system from Carnegie Mellon University confidently defeated professional poker players - a team consisting of the world's best players in unlimited Heads—Up poker. Matches were played in real time during the 20-day tournament, and the actions of the algorithm were counted on the Pittsburgh supercomputer;
      6.4.5.4.- It is no secret that in many other NARROW areas of human activity, AI systems significantly exceed human capabilities.

      6.4.5.5. NOTE: it would be interesting to compare the strengths and weaknesses of two different heuristic strategies in AI systems architecture of the neural network with working autonomously the software package, built on the methodology of TRIZ in an adversarial game in backgammon, checkers, chess, poker or other games.
Such a comparison would provide material for the mutual improvement of these technologies, and, possibly, for the creation of hybrid schemes of AI systems that combine or complement both heuristic methods.
Some obstacle to the creation of an autonomously working software package based on the TRIZ methodology is the insufficient formalization of this methodology in terms of mathematical logic ("Fuzzy Logic").

      6.4.6. (Plato laid the foundation of what is now known as "fuzzy logic" by pointing out that there is a third realm beyond true and false.
A mathematician of Polish origin, Jan Lukasiewicz, for the first time proposed a systematic alternative to Aristotle's two-digit logic and described 3-digit logic, the third meaning of which is "possibility".
Lukasevich developed the first system of multivalued logic - the three-valued logic of statements (1920), and with its help — a system of modal logic.
He developed an original language for formalizing logical expressions (the so-called "Polish Notation", which served as the basis for the more famous "Reverse Polish Notation").
As the third logical meaning of the statement, the meaning expressed by the words "probably", "neutral" was introduced.
About every statement in the Lukasevich system, we can say: it is either true (1), or false (0), or neutral (1/2).
Almost simultaneously with Lukasevich, Emil Leon Post (American mathematician and logician) introduced multivalued logic (1921).

Fuzzy logic is a branch of mathematics that is a generalization of classical logic and set theory, based on the concept of a fuzzy set, first introduced by a scientist (professor at the University of California) of Azerbaijani origin Lotfi A. Zadeh as an object with the function of belonging an element to a set, taking any values in the interval [0, 1], and not just 0 or 1 (in 1965 he published a fundamental work on the theory of fuzzy sets, in which he outlined the mathematical apparatus of this theory).
The "fuzzy logic" proposed by Lotfi A. Zadeh was an attempt to link mathematics with an intuitive way of communication, to which people turn, are guided in communication and interact with the world.
In 1973 , he proposed fuzzy logic later — the theory of soft computing and — the theory of computing with words and perceptions).




      6.4.7. Object 2 (or Process 2) is defined (the role of the conditional "Victim").
(The benefit of the 'Victim' is the attention, care, and compassion of others, as well as the ability to shift responsibility onto others.)
(In the role of 'Object 1' and 'Object 2' in various confrontations can become: territory, natural resources, space resources, power, influence, real estate, property, property rights, means of production, production technology, sales technology, exploitation technology, 'holy' places for various religions, 'holy monuments, gifts, relics, objects' for various religions, virtual digital images and objects in cyberspace, funds in non-cash digital accounts, tokens, stocks, futures, promissory notes, patents, trademarks and service marks, discoveries in science, know-how ideas, copyright objects, copyright rights, state and commercial secrets, secrets, digital encryption keys, commercial enterprise, vanity, awards in competitions and contests, money, artifacts, luxury goods, art objects, health, life, people, children, animals, etc.).

Subject 1 = Object 1 is defined (the conditional role of the "Persecutor", "Aggressor").
(The 'Pursuer' are looking for the 'wrong' in order to punish them and restore 'justice'.
They demonstrate 'righteous' anger, resentment, offended pride, irritation).

Subject 2 = Object 2 is defined (the role of the conditional "Rescuer, Peacemaker").
(Often, but not always, the Rescuer, Peacemaker's motive is a sense of self-worth and importance).
(The roles of 'Subject 1' and 'Subject 2' may be: states, political parties, communities of people (united on any basis, for example, religious, ethnic, subculture, profession, hobby, sports, relative, ...), commercial organizations, departments of organizations, employees, military personnel, criminogenic persons, criminogenic communities , student, teacher, boss, subordinate, coach, athlete, seller, buyer, strangers, neighbors, relatives, family members, 'parts of one personality' (intrapersonal conflicts), etc.).

► 1. 'Karpman's triangle' in relation to the problem of resolving a conflict (contradiction (or more detailed - INCONSISTENCY OF THE PARAMETERS OF INDIVIDUAL PARTS OF A COMPLEX SYSTEM)) in a non-technical sphere.   Object 2 (or Process 2) = Subject 2.   (Object 1 (or Process 1) = Subject 1).

      




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