Modeling of natural intelligence and dynamics of human thinking with the use of significant combinary space

Abstract

To create artificial intelligence, it is necessary to identify the properties of natural and develop a way to model it. There are many definitions of artificial intelligence in the literature, but there is no exact definition of this science yet. Differ-ent authors model natural intelligence differently. For example, artificial intelligence is defined as the ability of a digital computer to respond to information coming to its input devices, almost as a certain person reacts in the same infor-mation environment. This approach is based on the principle of self-organization of the model and is called heuristic. Human intelligence is also seen as an intuitive system. The creative process is accompanied by various manifestations of emotions, and decision-making in natural in-telligence is carried out in conditions of uncertainty of various kinds. Studies show that in the problems of this class it is related to: 1) incomplete input and current information; 2) with fuzzy input information; 3) with vaguely developed rules for processing and evaluating information. Significant combinatorial spaces, in particular significant information spaces, were used to model the dynamics of human thinking. The latter has a combinatorial nature and exists in two states: tranquility (convolute) and dynamics (deployed), which deployed from convolute. Collapsed is given by an information sign that contains the properties of the expanded space. Information is primarily related to the functioning of the human brain and is in the subconscious or consciousness in the form of images, fragments of speech and so on. The transfer of information (thoughts) is car-ried out with the help of deployed information space through the speech space, through gestures, movements, through writing, graphics. Depending on the type of uncertainty, the classification of natural intelligence is given. We believe that the con-cept of intelligence is associated with such operations as information processing and evaluation. Based on this, human intelligence is conditionally divided into three levels: 1) a person follows the rules, which are clearly formulated and described without analysis of their accuracy (learning rules); 2) the individual analyzes information for accuracy and develops its own rules of conduct under different conditions (rules of self-study); 3) the ability for independent of exist-ing rules of analysis, processing and evaluation of information for accuracy (rules of intuition). Partial realization of artificial intelligence is carried out through the use of self-tuning algorithms and modeling of self-organization processes in nature.