{"id":10334,"date":"2026-04-07T08:55:06","date_gmt":"2026-04-07T07:55:06","guid":{"rendered":"https:\/\/izvestiyakbncran.ru\/?page_id=10334"},"modified":"2026-04-10T09:23:57","modified_gmt":"2026-04-10T08:23:57","slug":"25-6-22-en","status":"publish","type":"page","link":"https:\/\/izvestiyakbncran.ru\/index.php\/en\/25-6-22-en\/","title":{"rendered":"25.6.22 En"},"content":{"rendered":"\n<h1 class=\"wp-block-heading has-lora-font-family\" style=\"font-size:22px\"><strong>Simulation model of a neurocognitive control system for an autonomous software agent performing cooperative behavior to automatically replenish ontologies<\/strong><\/h1>\n\n\n\n<p class=\"has-foreground-color has-text-color has-link-color has-lora-font-family has-extra-small-font-size wp-elements-def4469de44f5eee25842431f57731f6\" style=\"margin-top:0;margin-bottom:0;padding-top:0;padding-bottom:0\"><strong>Z.V. Nagoev, I.A. Pshenokova, O.V. Nagoeva, M.I. Anchekov, A. Z. Enes<\/strong><\/p>\n\n\n\n<p class=\"has-foreground-color has-text-color has-link-color has-lora-font-family has-extra-small-font-size wp-elements-86b70c892ee51d64e6bf0730e3274f25\" style=\"margin-top:0;margin-bottom:0;padding-top:0;padding-bottom:0\"><\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity is-style-wide\" style=\"margin-top:var(--wp--preset--spacing--20);margin-bottom:var(--wp--preset--spacing--20)\"\/>\n\n\n\n<div class=\"wp-block-group is-nowrap is-layout-flex wp-container-core-group-is-layout-d3328a80 wp-block-group-is-layout-flex\" style=\"margin-top:0;margin-bottom:0;padding-top:var(--wp--preset--spacing--20);padding-bottom:var(--wp--preset--spacing--20)\">\n<p class=\"has-text-color has-link-color has-lora-font-family has-extra-small-font-size wp-elements-fa99f84d8051eb763ab85c3007cdb1c2\" style=\"color:#5b1919;text-decoration:underline\"><strong><strong>Upload the full text<\/strong><\/strong><\/p>\n\n\n\n<div class=\"wp-block-group is-vertical is-layout-flex wp-container-core-group-is-layout-9151b400 wp-block-group-is-layout-flex\" style=\"min-height:0px;margin-top:0;margin-bottom:0;padding-top:0;padding-bottom:0\">\n<div class=\"wp-block-buttons is-content-justification-left is-layout-flex wp-container-core-buttons-is-layout-15bf754d wp-block-buttons-is-layout-flex\" style=\"margin-top:0;margin-bottom:0;padding-top:0;padding-right:0;padding-bottom:0;padding-left:0\">\n<div class=\"wp-block-button has-custom-width wp-block-button__width-100 is-style-outline is-style-outline--1\"><a class=\"wp-block-button__link has-background-background-color has-text-color has-background has-link-color has-border-color has-small-font-size has-custom-font-size wp-element-button\" href=\"http:\/\/izvestiyakbncran.ru\/wp-content\/uploads\/2026\/04\/22-nag-1.pdf\" style=\"border-color:#5b1919;border-style:solid;border-width:2px;border-radius:8px;color:#5b1919;padding-top:0.4rem;padding-right:var(--wp--preset--spacing--40);padding-bottom:0.4rem;padding-left:var(--wp--preset--spacing--40)\">PDF<\/a><\/div>\n<\/div>\n\n\n\n<div style=\"height:0px;width:0px\" aria-hidden=\"true\" class=\"wp-block-spacer wp-container-content-273e683f\"><\/div>\n<\/div>\n<\/div>\n\n\n\n<p class=\"has-foreground-color has-text-color has-link-color has-lora-font-family has-extra-small-font-size wp-elements-7c1b64d0315b3edfa1e718480138a633\" style=\"line-height:1.4\"><em><strong><strong>Abstract<\/strong>.<\/strong> <\/em>A circuit of the control system of an intelligent agent has been developed, which ensures the formation of semantic ontologies of the \u201cagent \u2013 environment\u201d system, combining on the basis of interneuron associations functional representations of the current observed states of the agent and statements of counterparties in the communicative environment. Based on the ontoneuromorphogenesis algorithm, axo-dendronal connections grow, which is aimed at reflecting the cause-and-effect relationships between events that describe the context of the situation, events that describe the subject of the statement, and the event that describes the statement itself. According to the results of experiments of the simulation model it was concluded that the multi-agent algorithm for the autonomous synthesis of functional systems of semantic ontologies based on the growth and development of neurocognitive architectures can be applied to any subject area.<\/p>\n\n\n\n<p class=\"has-foreground-color has-text-color has-link-color has-lora-font-family has-extra-small-font-size wp-elements-df03325adc83c022634de6b79d43432f\" style=\"line-height:1.4\"><\/p>\n\n\n\n<p class=\"has-foreground-color has-text-color has-link-color has-lora-font-family has-extra-small-font-size wp-elements-76cd51cb2b9ac7775843b8764381803c\" style=\"line-height:1.4\"><strong><em><strong>Keywords<\/strong>:<\/em><\/strong> control systems, intelligent agent, multi-agent system, cognitive architectures<\/p>\n\n\n\n<p class=\"has-foreground-color has-text-color has-link-color has-lora-font-family has-extra-small-font-size wp-elements-df03325adc83c022634de6b79d43432f\" style=\"line-height:1.4\"><\/p>\n\n\n\n<p class=\"has-foreground-color has-text-color has-link-color has-lora-font-family wp-elements-22fea9f755cb31c4efa8c999517d070e\" style=\"font-size:12px;line-height:1.4\"><strong><strong>For citation<\/strong>.<\/strong> Nagoev Z.V., Pshenokova I.A., Nagoeva O.V., Anchekov M.I., Enes A. Z. Simulation model of a neurocognitive control system for an autonomous software agent performing cooperative behavior to automatically replenish ontologies. <em>News of the Kabardino-Balkarian Scientific Center of RAS<\/em>. 2023. No. 6(116). Pp. 226\u2013234. DOI: 10.35330\/1991-6639-2023-6-116-226-234<\/p>\n\n\n\n<p class=\"has-foreground-color has-text-color has-link-color has-lora-font-family wp-elements-17c3333a0b1db39b7fa4a3e1a1572bc4\" style=\"font-size:12px;line-height:1.4\"><\/p>\n\n\n\n<details class=\"wp-block-details has-foreground-color has-text-color has-link-color has-lora-font-family has-extra-small-font-size wp-elements-4b79531cae92bee8653bfb0aa60e1624 is-layout-flow wp-container-core-details-is-layout-0ab540ad wp-block-details-is-layout-flow\" style=\"font-style:normal;font-weight:700;line-height:1.5\"><summary><strong>R<\/strong>eferences<\/summary>\n<ol style=\"margin-top:0;margin-bottom:0\" class=\"wp-block-list\">\n<li style=\"font-style:normal;font-weight:400\">Lan M., Xu J. Ontology feature extraction via vector learning algorithm and applied to similarity measuring and ontology mapping. <em>IAENG International Journal of Computer Science<\/em>. Vol. 43(1). Pp. 10\u201319.<\/li>\n\n\n\n<li style=\"font-style:normal;font-weight:400\">Somodevilla M., Ayala D., Pineda I. An overview on ontology learning tasks. Comput. Sist. Vol. 22(1). Pp. 137\u2013146.<\/li>\n\n\n\n<li style=\"font-style:normal;font-weight:400\">Alobaidi M., Malik K.M. Linked open data-based framework for automatic biomedical ontology generation. <em>BMC bioinformatics<\/em>. 2018. Vol. 19(1). Pp. 3\u201319.<\/li>\n\n\n\n<li style=\"font-style:normal;font-weight:400\">Asim M.N. et al. A survey of ontology learning techniques and applications. Database. Vol. 2018. P. 101.<\/li>\n\n\n\n<li style=\"font-style:normal;font-weight:400\">Ma Z., Cheng H. et al. Automatic Construction of OWL Ontologies From Petri Nets. <em>International Journal on Semantic Web and Information Systems (IJSWIS).<\/em> 2019. Vol. 15(1). Pp. 21\u201351.<\/li>\n\n\n\n<li style=\"font-style:normal;font-weight:400\">Maynard D., Funk A., Peters W. Using lexico-syntactic ontology design patterns for ontology creation and population. <em>Proc. of the Workshop on Ontology Patterns<\/em>. 2009. Vol. 516. Pp. 39\u201352.<\/li>\n\n\n\n<li style=\"font-style:normal;font-weight:400\">Dzyubanenko A.A., Rabin A.V. Application of the method of metaontologies in the intellectual analysis of text resources considering the fuzziness and blurring of images of natural language units. <em>AIP Conference Proceedings<\/em>. 2022. Vol. 2647. https:\/\/doi.org\/10.1063\/5.0124340<\/li>\n\n\n\n<li style=\"font-style:normal;font-weight:400\">Elnagar S., Yoon V., Thomas M. A. An automatic ontology generation framework with an organizational perspective. arXiv:2201.05910. 2022.<\/li>\n\n\n\n<li style=\"font-style:normal;font-weight:400\">Kumar N., Kumar M., Singh M. Automated ontology generation from a plain text using statistical and NLP techniques. <em>International Journal of System Assurance Engineering and Management<\/em>. 2016. Vol. 7. Pp. 282\u2013293.<\/li>\n\n\n\n<li style=\"font-style:normal;font-weight:400\">Cahyani D.E., Wasito I. Automatic ontology construction using text corpora and ontology design patterns (ODPs) in Alzheimer\u2019s disease. <em>J. Ilmu Komputer dan Informasi<\/em>. 2017. Vol. 10(2). Pp. 59\u201366.<\/li>\n\n\n\n<li style=\"font-style:normal;font-weight:400\">Jabla R., Khemaja M., Buendia F., Faiz S. Automatic Ontology-Based Model Evolution for Learning Changes in Dynamic Environments. <em>Applied Sciences<\/em>. 2021. Vol. 11(22). P. 10770. https:\/\/doi.org\/10.3390\/app112210770<\/li>\n\n\n\n<li style=\"font-style:normal;font-weight:400\">Nagoev Z.V. <em>Intellektika, ili Myshleniye v zhivykh i iskusstvennykh sistemakh<\/em> [Intelligence, or thinking in living and artificial systems]. Nalchik: Izdatel&#8217;stvo KBNTS RAN, 2013. 232 p. (In Russian)<\/li>\n\n\n\n<li style=\"font-style:normal;font-weight:400\">Nagoev Z., Nagoeva O., Gurtueva I. Multi-agent neurocognitive models of semantics of spatial localization of events. <em>Cognitive Systems Research<\/em>. 2020. Vol. 59. Pp. 91\u2013102.<\/li>\n\n\n\n<li style=\"font-style:normal;font-weight:400\">Bzhikhatlov K.Ch., Kankulov S.A., Malyshev D.A. et al. Interactive formation of spatial ontologies of an autonomous robot based on neurocognitive models of semantics. <em>Materialy XVI vserossijskoj nauchno-prakticheskoj konferencii i XII molodezhnoj shkoly-seminara \u00abPerspektivnye sistemy i zadachi upravleniya\u00bb<\/em> [Materials of the XVI All-Russian Scientific and Practical Conference and the XII Youth School-Seminar \u201cAdvanced Systems and Management Problems\u201d]. Rostov-na-Dony, 2021. Pp. 147\u2013154. (In Russian)<\/li>\n\n\n\n<li style=\"font-style:normal;font-weight:400\">Nagoev Z., Pshenokova I., Nagoeva O., Sundukov Z. Learning algorithm for an intelligent decision making system based on multi-agent neurocognitive architectures. <em>Cognitive Systems Research<\/em>. 2021. Vol. 66. Pp. 82\u201388.<\/li>\n\n\n\n<li style=\"font-style:normal;font-weight:400\">Nagoev Z.V. Multi-agent existential mappings and functions. <em>News of the KabardinoBalkarian Scientific Center of RAS<\/em>. 2013. No. 4(54). \u0420p. 63\u201371. (In Russian)<\/li>\n<\/ol>\n<\/details>\n\n\n\n<details class=\"wp-block-details has-foreground-color has-text-color has-link-color has-lora-font-family has-extra-small-font-size wp-elements-1f3599771094271244075d5fd8391760 is-layout-flow wp-container-core-details-is-layout-5dafc681 wp-block-details-is-layout-flow\" style=\"font-style:normal;font-weight:700;line-height:1.5\"><summary><strong>Information about the authors<\/strong><\/summary>\n<div class=\"wp-block-group is-vertical is-layout-flex wp-container-core-group-is-layout-b291ae12 wp-block-group-is-layout-flex\" style=\"min-height:0px;margin-top:0;margin-bottom:0;padding-top:var(--wp--preset--spacing--20);padding-right:var(--wp--preset--spacing--40);padding-bottom:var(--wp--preset--spacing--20);padding-left:var(--wp--preset--spacing--40)\">\n<p style=\"font-style:normal;font-weight:400\"><strong>Nagoev Zalimkhan Vyacheslavovich<\/strong>, Candidate of Technical Sciences, General Director of the Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences;<br>360000, Russia, Nalchik, 37-a I. Armand street;<br>zaliman@mail.ru, ORCID: https:\/\/orcid.org\/0000-0001-9549-1823<br><strong>Pshenokova Inna Auesovna<\/strong>, Candidate of Physical and Mathematical Sciences, Head of the Laboratory \u201cIntelligent Living Environments\u201d, Institute of Computer Science and Problems of Regional Management \u2013 branch of Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences;<br>360000, Russia, Nalchik, 37-a I. Armand street;<br>pshenokova_inna@mail.ru, ORCID: https:\/\/orcid.org\/0000-0003-3394-7682<br><strong>Nagoeva Olga Vladimirovna<\/strong>, Researcher of the Department \u201cMultiagent Systems\u201d, Institute of Computer Science and Problems of Regional Management \u2013 branch of Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences;<br>360000, Russia, Nalchik, 37-a I. Armand street;<br>nagoeva_o@mail.ru, ORCID: https:\/\/orcid.org\/0000-0003-2341-7960<br><strong>Anchekov Murat Inusovich<\/strong>, Researcher of the Laboratory \u201cMolecular Selection and Biotechnology\u201d, Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences;<br>360000, Russia, Nalchik, 224 Kirov street;<br>murat.antchok@gmail.com, ORCID: https:\/\/orcid.org\/0000-0002-8977-797X<br><strong>Enes Ahmed Zulfikar<\/strong>, Junior Researcher of the Laboratory \u201cComputational Linguistics\u201d, Institute of Computer Science and Problems of Regional Management \u2013 branch of Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences;<br>360000, Russia, Nalchik, 37-a I. Armand street;<br>ahmedenes@mail.ru, ORCID: https:\/\/orcid.org\/0000-0003-3633-4910<\/p>\n\n\n\n<p style=\"font-style:normal;font-weight:400\"><br><\/p>\n\n\n\n<p style=\"font-style:normal;font-weight:400\"><\/p>\n\n\n\n<p style=\"font-style:normal;font-weight:400\"><\/p>\n\n\n\n<p style=\"font-style:normal;font-weight:400\"><\/p>\n\n\n\n<p style=\"font-style:normal;font-weight:400\"><\/p>\n\n\n\n<p style=\"font-style:normal;font-weight:400\"><\/p>\n<\/div>\n<\/details>\n","protected":false},"excerpt":{"rendered":"<p>Simulation model of a neurocognitive control system for an autonomous software agent performing cooperative behavior to automatically replenish ontologies Z.V. Nagoev, I.A. Pshenokova, O.V. Nagoeva, M.I. Anchekov, A. Z. Enes Upload the full text Abstract. A circuit of the control system of an intelligent agent has been developed, which ensures the formation of semantic ontologies [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"wp-custom-template-home","meta":{"footnotes":""},"class_list":["post-10334","page","type-page","status-publish","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.5 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>25.6.22 En - \u0418\u0417\u0412\u0415\u0421\u0422\u0418\u042f \u041a\u0410\u0411\u0410\u0420\u0414\u0418\u041d\u041e-\u0411\u0410\u041b\u041a\u0410\u0420\u0421\u041a\u041e\u0413\u041e \u041d\u0410\u0423\u0427\u041d\u041e\u0413\u041e \u0426\u0415\u041d\u0422\u0420\u0410 \u0420\u0410\u041d\u00bb<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/izvestiyakbncran.ru\/index.php\/en\/25-6-22-en\/\" \/>\n<meta property=\"og:locale\" content=\"ru_RU\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"25.6.22 En - \u0418\u0417\u0412\u0415\u0421\u0422\u0418\u042f \u041a\u0410\u0411\u0410\u0420\u0414\u0418\u041d\u041e-\u0411\u0410\u041b\u041a\u0410\u0420\u0421\u041a\u041e\u0413\u041e \u041d\u0410\u0423\u0427\u041d\u041e\u0413\u041e \u0426\u0415\u041d\u0422\u0420\u0410 \u0420\u0410\u041d\u00bb\" \/>\n<meta property=\"og:description\" content=\"Simulation model of a neurocognitive control system for an autonomous software agent performing cooperative behavior to automatically replenish ontologies Z.V. 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Nagoev, I.A. Pshenokova, O.V. Nagoeva, M.I. Anchekov, A. Z. Enes Upload the full text Abstract. 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