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

• Published in: Scientific and technical information processing Vol. 48; no. 5; pp. 333 - 341
• Main Authors: Melekhin, V. B., Khachumov, M. V.
• Format: Journal Article
• Language: English
• Published: Moscow Pleiades Publishing 01.12.2021; Springer Nature B.V
• Subjects: Computer Science; Computer Systems Organization and Communication Networks; Decision making; Intelligent systems; Knowledge representation; Networks; Semantics; Uncertainty; fuzzy semantic network; planning of behavior; problem environment; uncertainty conditions; knowledge representation; autonomous intelligent system
• ISSN: 0147-6882; 1934-8118
• DOI: 10.3103/S0147688221050051

— 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.