Abstract
The article reviews the functional and structural organization of the Multi-Agent System of Knowledge Representation and Processing (MASKRP). The architecture of the MASKRP, the models of reactive and cognitive software agents are described. The examples of the interaction, states and transitions diagrams of the software agents, the systems of rules and the queries of the problem-oriented multi-agent solver are given. A classical logic solver and the multi-agent solver, which is developed on the basis of the software agents models described in this article, are compared. The results of fuzzy queries to the knowledge base, which were realized according to the sets of fuzzy rules and membership functions specified in the example, are shown. The results demonstrate the practical viability and efficiency of the presented approach to implementation of a multi-agent system based on fuzzy knowledge. At the heart of design decisions at creation of the MASKRP the requirement of support of users of different competence level is put. To support the process of knowledge acquisition and user’s comfort setting up mechanisms of automated reasoning developed the problem-oriented toolkit of visual design.
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Zaytsev, E.I., Khalabiya, R.F., Stepanova, I.V., Bunina, L.V. (2020). Multi-Agent System of Knowledge Representation and Processing. In: Kovalev, S., Tarassov, V., Snasel, V., Sukhanov, A. (eds) Proceedings of the Fourth International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’19). IITI 2019. Advances in Intelligent Systems and Computing, vol 1156. Springer, Cham. https://doi.org/10.1007/978-3-030-50097-9_14
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