S.G. Vorona1, V.V. Lisickii2, A.V. Stolbov3

1−3 Mozhaisky Military Space Academy (St. Petersburg, Russia)

The article deals with the methodology of solving non-formalized problems. The first methodology represents the traditional approach to the description of the problem domain model (MPO) and it is characterized by a significant operational semantics. The second description methodology represents a new direction in computer science − artificial intelligence. Any problem for which the solution algorithm is unknown, a priori refers to artificial intelligence. An algorithm is understood as the entire sequence of specified actions that are well defined and can be performed on a computer.

The knowledge model is a means of describing the logic and data of the problem being solved. Since the knowledge about the subject area may be inaccurate, incomplete, or unclear, and the subject areas are different, the logic used in the description may also be different. The problem to be solved is presented in the form of rules (statements) and a request, the validity of which should be established or refuted. The solution of the problem is reduced to finding out the logical sequence (derivability) of the target formula from a given set of rules.

The most popular knowledge models for creating ES are production models.

The frame model, or the model of knowledge representation, based on the frame theory, is a psychological model of human memory and consciousness systematized in the form of a single theory

The semantic network model is a knowledge representation model based on the semantic network method. The described models are only a small part of the applied methods for solving unformalized problems.

Vorona S.G., Lisickii V.V., Stolbov A.V. Unformalized tasks and methodology of their solution. Nonlinear World. 2021. V. 19. № 3. 2021. P. 18−28. DOI: https://doi.org/10.18127/j20700970-202103-02 (In Russian)

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