Features of information modeling based on swarm metaphors

Abstract

The procedure of information modeling based on metaphors of swarms in an intelligent information environment, its features and composition are considered. For the formation of the concept in the intellectual environment of construction, the possibility of using the swarm particle algorithm of metaphorical optimization in cognitive technologies to normalize the concept and its features of the intellectual within the limits of the defined issues is determined and substantiated. A promising direction for solving complex optimization tasks is heuristics, which is determined by the objective ambiguity of the task statement and involves choosing from a set of solutions based on the relations of analogy, similarity, similarity. In order to understand the ontology of the subject area, an analysis of the choice of metaphor, which provides effective solutions to specific problems due to evolutionary origin, was carried out. The metaphor helps to effectively build fuzzy classifiers, on the basis of which to informationally determine the areas of maximum overlap of concepts based on the results of processing the information of fuzzy prototypes of the concepts of the assumed fuzzy data cluster of the functioning of the basic definition based on the basic information for the swarm. The fundamental property of the swarm is the information exchange between the particles of the swarm, which connects the particles in the swarm as such, which realizes the asymmetry of the information exchange for the particle of the swarm. At the same time, a family of solutions for a collection of swarms of particles based on basic information and connected information spaces generates a solution as the most general basic solution. An analysis of the features of information modeling based on metaphors of swarms was carried out. The peculiarities of concepts of the ontology of the subject area for choosing a metaphor are determined.