The use of metaknowledge in a decision-making support system implemented in the functional neural network formalism

Abstract

This paper describes the development of the functional-neural-network (FN-network) formalism, which was worked out to create a range of information systems for the intelligent computer processing of heterogeneous data from various information sources and automated decision-making support systems. It considers the limitations of this formalism in solving the tasks when the time intervals at which a solution is searched for are given in the form of indefinite variables. A method is proposed for avoiding these limitations by entering knowledge about the internal structure of data (metaknowledge) on these intervals into the context of a solution and it is shown that the use of metaknowledge not only solves the problem, but also improves the efficiency of searching for a solution by attracting additional information from a knowledge base and the context of a task.