Fuzzy Semantic Networks as a Knowledge Representation Model of Autonomous Intelligent Systems
— 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 system...
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| Veröffentlicht in: | Scientific and technical information processing 2021-12, Vol.48 (5), p.333-341 |
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| container_title | Scientific and technical information processing |
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| creator | Melekhin, V. B. Khachumov, M. V. |
| description | —
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. |
| doi_str_mv | 10.3103/S0147688221050051 |
| format | Article |
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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.</description><identifier>ISSN: 0147-6882</identifier><identifier>EISSN: 1934-8118</identifier><identifier>DOI: 10.3103/S0147688221050051</identifier><language>eng</language><publisher>Moscow: Pleiades Publishing</publisher><subject>Computer Science ; Computer Systems Organization and Communication Networks ; Decision making ; Intelligent systems ; Knowledge representation ; Networks ; Semantics ; Uncertainty</subject><ispartof>Scientific and technical information processing, 2021-12, Vol.48 (5), p.333-341</ispartof><rights>Allerton Press, Inc. 2021. ISSN 0147-6882, Scientific and Technical Information Processing, 2021, Vol. 48, No. 5, pp. 333–341. © Allerton Press, Inc., 2021. Russian Text © The Author(s), 2020, published in Iskusstvennyi Intellekt i Prinyatie Reshenii, 2020, No. 3, pp. 61–72.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c316t-c7dd97130ab7af36e7e753fe45b3657fbb0e2ee3b45eec071dd412f522e2b0e83</citedby><cites>FETCH-LOGICAL-c316t-c7dd97130ab7af36e7e753fe45b3657fbb0e2ee3b45eec071dd412f522e2b0e83</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.3103/S0147688221050051$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.3103/S0147688221050051$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,777,781,27905,27906,41469,42538,51300</link.rule.ids></links><search><creatorcontrib>Melekhin, V. B.</creatorcontrib><creatorcontrib>Khachumov, M. V.</creatorcontrib><title>Fuzzy Semantic Networks as a Knowledge Representation Model of Autonomous Intelligent Systems</title><title>Scientific and technical information processing</title><addtitle>Sci. Tech. Inf. Proc</addtitle><description>—
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.</description><subject>Computer Science</subject><subject>Computer Systems Organization and Communication Networks</subject><subject>Decision making</subject><subject>Intelligent systems</subject><subject>Knowledge representation</subject><subject>Networks</subject><subject>Semantics</subject><subject>Uncertainty</subject><issn>0147-6882</issn><issn>1934-8118</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNp1kEtLAzEUhYMoWKs_wF3A9Wiek5llKT6KVcHqUoZ53JSpM0lNMpT215tSwYUIF87ifOdcOAhdUnLNKeE3C0KFSrOMMUokIZIeoRHNuUgySrNjNNrbyd4_RWferyKRMpGP0MfdsNtt8QL60oS2xs8QNtZ9elzGw4_GbjpoloBfYe3AgwllaK3BT7aBDluNJ0OwxvZ28HhmAnRdu4wQXmx9gN6foxNddh4ufnSM3u9u36YPyfzlfjadzJOa0zQktWqaXFFOykqVmqegQEmuQciKp1LpqiLAAHglJEBNFG0aQZmWjAGLVsbH6OrQu3b2awAfipUdnIkvC5YKImWeExIpeqBqZ713oIu1a_vSbQtKiv2KxZ8VY4YdMj6yZgnut_n_0DeTOHT-</recordid><startdate>20211201</startdate><enddate>20211201</enddate><creator>Melekhin, V. B.</creator><creator>Khachumov, M. V.</creator><general>Pleiades Publishing</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20211201</creationdate><title>Fuzzy Semantic Networks as a Knowledge Representation Model of Autonomous Intelligent Systems</title><author>Melekhin, V. B. ; Khachumov, M. V.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c316t-c7dd97130ab7af36e7e753fe45b3657fbb0e2ee3b45eec071dd412f522e2b0e83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Computer Science</topic><topic>Computer Systems Organization and Communication Networks</topic><topic>Decision making</topic><topic>Intelligent systems</topic><topic>Knowledge representation</topic><topic>Networks</topic><topic>Semantics</topic><topic>Uncertainty</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Melekhin, V. B.</creatorcontrib><creatorcontrib>Khachumov, M. V.</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Scientific and technical information processing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Melekhin, V. B.</au><au>Khachumov, M. V.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Fuzzy Semantic Networks as a Knowledge Representation Model of Autonomous Intelligent Systems</atitle><jtitle>Scientific and technical information processing</jtitle><stitle>Sci. Tech. Inf. Proc</stitle><date>2021-12-01</date><risdate>2021</risdate><volume>48</volume><issue>5</issue><spage>333</spage><epage>341</epage><pages>333-341</pages><issn>0147-6882</issn><eissn>1934-8118</eissn><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.</abstract><cop>Moscow</cop><pub>Pleiades Publishing</pub><doi>10.3103/S0147688221050051</doi><tpages>9</tpages></addata></record> |
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| language | eng |
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| subjects | Computer Science Computer Systems Organization and Communication Networks Decision making Intelligent systems Knowledge representation Networks Semantics Uncertainty |
| title | Fuzzy Semantic Networks as a Knowledge Representation Model of Autonomous Intelligent Systems |
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