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Scientific and Technical Information Processing

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01.12.2021

Fuzzy Semantic Networks as a Knowledge Representation Model of Autonomous Intelligent Systems

verfasst von: V. B. Melekhin, M. V. Khachumov

Erschienen in: Scientific and Technical Information Processing | Ausgabe 5/2021

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Abstract—

This paper considers the main characteristics of goal-oriented behavior displayed by autonomous intelligent systems in conditions of a problem environment different in the degree of a priori uncertainty. A model is developed for declarative knowledge representation in autonomous intelligent systems regardless of the specific subject area based on active and passive fuzzy semantic networks. The operations of comparing fuzzy semantic networks with each other are considered, which enable the organization of effective decision making in the process of planning goal-oriented behavior under conditions of uncertainty. The operations of decomposition, composition, and generalization of fuzzy semantic networks were developed, which serve to organize the behavioral planning for autonomous intelligent systems in the process of solving complex problems, accompanied by a formal description of current situations of a problem environment with a large dimension.

Vorheriger Artikel A System–Object Approach to Determinant Analysis of Complex Systems

Nächster Artikel Reduction of Attribute Space Dimensionality: the SOCRATES Method

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Titel: Fuzzy Semantic Networks as a Knowledge Representation Model of Autonomous Intelligent Systems
verfasst von: V. B. Melekhin
M. V. Khachumov
Publikationsdatum: 01.12.2021
Verlag: Pleiades Publishing
Erschienen in: Scientific and Technical Information Processing / Ausgabe 5/2021
Print ISSN: 0147-6882
Elektronische ISSN: 1934-8118
DOI: https://doi.org/10.3103/S0147688221050051

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