Читать книгу Responsible Sustainability Model. Polyvalent model & Virtual economy - - Страница 11

Ideas about individual and family development are directly related to the general understanding of the idea of the environment. In this case, the process of developing ideas about the individual and the family is much more complicated than the process of developing ideas about the world.

At the physiological level, emotions are feelings, feelings as causes, actions, and effects, which are the simplest physical and chemical reactions available for digital processing. At the same time, it is a huge universe of infinite information, which is defined as a set of the simplest physical and chemical reactions.

The polyvalent model aims to provide an interpretation view and predict the behaviour of individuals and groups in the context of the perception and interpretation of the information environment in which they are constantly involved, as well as to recognise, interpret and predict behaviour. The structure of each living organism is characterised by the presence of endomorphic and ectomorphic systems, each of which performs two main functions: the formation of perception and assessment of the current situation. Due to the endomorphic system, emotions are generated, as well as sensations and stimuli are generated. As a result of cognitive processes that are carried out by the endomorphic system, all reactions to external stimuli are carried out on the basis of the data received from them.

Like any task, it consists of three main components: information, a problem, and a solution chosen for the task. Any change in one of the components of the system will lead to changes in other components if the change occurs in one of them.

As a starting point for creating a collaborative program, each model and problem needs to be analysed with a set of methods and tools that will help highlight the main components of the problem and their interrelationships, as well as the interactions between them.

A single program of a polyvalent model, which will use data mining methods in the field of computational intelligence, will be able to combine the individual components of the problem. Another method is the use of neural networks, which are especially useful in this case, since they are able to process huge amounts of information. Their implementation in the work will be divided into two parts: data input and output, which will be performed independently.

The inference method will produce an inference about the behaviour of individuals and groups under various circumstances, while the input method will provide data and information about the state of the individual or group, the quantity and quality of which can be changed by the course of events, and the content of which is often difficult to assess.

The polyvalent model develops a system that can receive information and analyse it as a result of the operation of a neural network, and then create a decision-making system.

All cognitive system models can be divided into two categories: models that separate problem and solution, and models that combine problem and solution. Both categories have their advantages and disadvantages. The advantage of separating the problem and the solution is the ability to identify the external and internal conditions of the problem, which are important for understanding the factors that influence the behaviour of an individual or group. The disadvantage is the difficulty in understanding the relationship between the problem and the solution, which also affects the behaviour of an individual or group. In a unified approach, the problem and solution are combined into one, but this limits the ability to understand the relationship between the problem and the solution. In both approaches, it is important to identify the main components of the problem that determine the nature of the problem. The first type of analysis is designed to separate the components from the environment and from the observer, and the second type is to separate the components from the external environment.

The problem of establishing the effectiveness of cooperation is characterised by the fact that it is possible to cooperate with a person whose origin, culture and cultural reference points do not differ from the situation under consideration. It is very difficult to establish communication with such a person, and, as a result, cooperation is established with great difficulty, if at all.

The problem of establishing the effectiveness of cooperation is a key problem for most areas of human activity and is a necessary foundation for building any human activity.

The uniqueness of the method of analysis and evaluation lies in the presence of a computerised component in the development of the cooperation system. The architecture is based on the use of artificial intelligence tools. The task is to create a system with the following characteristics:

1) The system will be integrated into the information environment of the participants in the cooperation process.

2) The system of cooperation will not be static.

After the analysis, the desired goal of the system can be formulated. This goal will help find a solution to the current problem. A set of tools and methods is also needed to prepare a program of interaction with the system, which will change the parameters of the solution of the problem in order to achieve an increase in efficiency.

The main result of the developed cooperation program will be a change in the parameters for solving the problem. As a result, this will lead to a change in the values of the parameters, the end result of which will be a change in the behaviour of the system.

To achieve this goal, it is necessary to identify all the components that make up the system. Endomorphic and ectomorphic systems are two independent systems that are part of the information environment. From a technological point of view, these two systems are represented by interfaces that are designed to create a combination of these two systems into one system.

In other words, a set of methods and tools is created to isolate the main components of the problem and their relationships, as well as the interactions between them, which will determine the solution to the problem.

The purpose of a polyvalent model is to develop methods and tools for analysing dynamic systems, creating models and extracting them from existing models, creating tools for forecasting and creating systems for coordinating a team of experts. The polyvalent model is designed to be applied to the analysis of any problem that requires the interaction of specialists and the creation of various options for solving the problem.