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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.