{"id":9730,"date":"2026-04-02T12:26:05","date_gmt":"2026-04-02T11:26:05","guid":{"rendered":"https:\/\/izvestiyakbncran.ru\/?page_id=9730"},"modified":"2026-04-06T14:12:23","modified_gmt":"2026-04-06T13:12:23","slug":"25-5-1-en","status":"publish","type":"page","link":"https:\/\/izvestiyakbncran.ru\/index.php\/en\/25-5-1-en\/","title":{"rendered":"25.5.1 En"},"content":{"rendered":"\n

Formal genome model of a general artificial intelligence agent based on multi-agent neurocognitive architectures<\/strong><\/h1>\n\n\n\n

M.I. Anchekov, A.Z. Apshev, K.Ch. Bzhikhatlov, S.A. Kankulov,
Z.V. Nagoev, O.V. Nagoeva, I.A. Pshenokova, A.A. Khamov, A.Z. Enes<\/strong><\/p>\n\n\n\n

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Abstract<\/strong>:<\/strong> <\/em>The relevance of the research is determined by the need to develop and programmatically implement artificial general intelligence agents capable of self-learning based on adaptation to the conditions of solving problems of the universal spectrum based on the ontoepiphilosociogenetic learning process. The research is aimed at developing a formalization of a general artificial intelligence agent suitable for creating its simulation model. A formalization of an intelligent agent is constructed based on two-level multi-agent neurocognitive architectures using an automatic description and multi-agent functions. A formal description of the genomes of neuron agents as part of a multi-agent neurocognitive architecture and the genotype of an intelligent agent has been developed. The resulting formalization can be used to create software for general artificial intelligence systems.<\/p>\n\n\n\n

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Keywords<\/strong>:<\/em><\/strong>general artificial intelligence, multi-agent systems, neurocognitive architectures, abstract deterministic automata, multi-generational optimization, genetic algorithms, multi-agent functions<\/p>\n\n\n\n

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For citation<\/strong>.<\/strong> Anchekov M.I., Apshev A.Z., Bzhikhatlov K.Ch. et al. Formal genome model of a general artificial intelligence agent based on multi-agent neurocognitive architectures. News of the Kabardino-Balkarian Scientific Center of RAS<\/em>. 2023. No. 5(115). Pp. 11\u201324. DOI: 10.35330\/1991-6639-2023-5-115-11-24<\/p>\n\n\n\n

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R<\/strong>eferences<\/summary>\n
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  1. Anchekov M.I., Bzhikhatlov K.Ch., Nagoev Z.V. et al. Onto-episociophilogenetic development of general artificial intelligence systems based on multi-agent neurocognitive architectures. News of Kabardino-Balkarian Scientific Center of RAS<\/em>. 2022. No. 6(110). Pp. 61\u201375. DOI: 10.35330\/1991-6639-2022-6-110-61-75. (In Russian)<\/li>\n\n\n\n
  2. Apshev A.Z., Atalikov B.A., Kankulov S.A. et al. Ontophylogenetic algorithms for the synthesis of phenotypes of intelligent software agents for use in multigenerational optimization problems control neuro-cognitive architectures. News of Kabardino-Balkarian Scientific Center of RAS<\/em>. 2022. No. 6(110). Pp. 76\u201391. DOI: 10.35330\/1991-6639-2022-6-110-76-91. (In Russian)<\/li>\n\n\n\n
  3. Nagoev Z., Nagoeva O., Anchekov M. et al. The symbol grounding problem in the system of general artificial intelligence based on multi-agent neurocognitive architecture. Cognitive Systems Research<\/em>. 2023. No. 79. Pp. 71\u201384.<\/li>\n\n\n\n
  4. Nagoev Z.V. Intellektika, ili myshleniye v zhivykh i iskusstvennykh sistemakh<\/em> [Intelligence, or thinking in living and artificial systems]. Nalchik: Izdatel’stvo KBNTS RAN, 232 p. (In Russian)<\/li>\n\n\n\n
  5. Nagoev Z.V. Ontoneuromorphogenetic modeling. News of Kabardino-Balkarian Scientific Center of RAS. 2013. No. 4(54). Pp. 46\u201356. (In Russian)<\/li>\n\n\n\n
  6. Holland J.H. Adaptation in natural and artificial systems. University of Michigan Press. Ann Arbor, 1975.<\/li>\n\n\n\n
  7. Nagoev Z.V., Nagoeva O.V. Obosnovaniye simvolov i mul’tiagentnyye neyrokognitivnyye modeli semantiki yestestvennogo yazyka<\/em> [Justification of symbols and multi-agent neurocognitive models of natural language semantics]. Nalchik: Izdatel’stvo KBNTS RAN, 150 p. (In Russian)<\/li>\n\n\n\n
  8. Stuart Russell, Peter Norvig. Artificial Intelligence: A Modern Approach (AIMA). 2nd ed. Moscow: Williams, 2007. 1424 p.<\/li>\n\n\n\n
  9. Nagoev Z. V. Multi-agent existential mappings and functions. News of Kabardino-Balkarian Scientific Center of RAS<\/em>. 2013. No. 4(54). Pp. 63\u201371. (In Russian)<\/li>\n\n\n\n
  10. Anchekov M.I., Bzhikhatlov K.Ch., Leshkenov A.M. High-performance systems for phenotyping agricultural crops. News of Kabardino-Balkarian Scientific Center of RAS<\/em>. 2022. No. 5(109). Pp. 19\u201324. DOI: 10.35330\/1991-6639-2022-5-109-19-24. (In Russian)<\/li>\n\n\n\n
  11. Anchekov M.I., Bogotova Z.I., Pshenokova I.A. et al. Collaborative breeding system based on a consortium of heterogeneous intelligent agents. News of Kabardino-Balkarian Scientific Center of RAS<\/em>. 2022. No. 5(109). Pp. 25\u201337. DOI: 10.35330\/1991-6639-2022-5-109-25-37. (In Russian)<\/li>\n<\/ol>\n<\/details>\n\n\n\n
    Information about the authors<\/strong><\/summary>\n
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    Anchekov Murat Inusovich<\/strong>, Researcher of the Laboratory \u201cMolecular selection and biotechnology\u201d, Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences;
    360000, Russia, Nalchik, 224 Kirov street;
    murat.antchok@gmail.com, ORCID: https:\/\/orcid.org\/0000-0002-8977-797X
    Apshev Artur Zaurovich<\/strong>, Trainee researcher of the Laboratory \u201cNeurocognitive Autonomous Intelligent Systems\u201c of the Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences;
    360002, Russia, Nalchik, 2 Balkarov street;
    apshev@mail.ru, ORCID: https:\/\/orcid.org\/0000-0002-7628-0825
    Bzhikhatlov Kantemir Chamalovich<\/strong>, Candidate of Physical-Mathematical Sciences, Head of the Laboratory \u201cNeurocognitive Autonomous Intelligent Systems\u201d of the Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences;
    360002, Russia, Nalchik, 2 Balkarov street;
    haosit13@mail.ru, ORCID: https:\/\/orcid.org\/0000-0003-0924-0193
    Kankulov Sultan Akhmedovich<\/strong>, Trainee researcher of the Laboratory \u201cIntellectual Habitats\u201d of the Institute of Computer Science and Problems of Regional Management \u2013 branch of Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences;
    360000, Russia, Nalchik, 37-a I. Armand street;
    skankulov@mail.ru, ORCID: https:\/\/orcid.org\/0000-0002-2996-7376
    Nagoev Zalimkhan Vyacheslavovich<\/strong>, Candidate of Technical Sciences, General Director of the Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences;
    360000, Russia, Nalchik, 37-a I. Armand street;
    zaliman@mail.ru, ORCID: https:\/\/orcid.org\/0000-0001-9549-1823
    Nagoeva Olga Vladimirovna<\/strong>, Researcher of the Department \u201cMultiagent Systems\u201d of the Institute of Computer Science and Problems of Regional Management \u2013 branch of Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences;
    360000, Russia, Nalchik, 37-a I. Armand street;
    nagoeva_o@mail.ru, ORCID: https:\/\/orcid.org\/0000-0003-2341-7960
    Pshenokova Inna Auesovna<\/strong>, Candidate of Physical and Mathematical Sciences, Leading Researcher of the Laboratory \u201cNeurocognitive autonomous intelligent systems\u201d of the Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences;
    360002, Russia, Nalchik, 2 Balkarov street;
    pshenokova_inna@mail.ru, ORCID: https:\/\/orcid.org\/0000-0003-3394-7682
    Khamov Anzor Azamatgerievich<\/strong>, Junior researcher of the Laboratory \u201cMolecular selection and biotechnology\u201d of the Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences;
    360000, Russia, Nalchik, 224 Kirov street;
    opitnoe2014@mail.ru, ORCID: https:\/\/orcid.org\/0000-0003-3269-4572
    Enes Akhmed Zyulfikar<\/strong>, Trainee researcher of the Laboratory \u201cIntellectual Habitats\u201d of the Institute of Computer Science and Problems of Regional Management \u2013 branch of the Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences;
    360000, Russia, Nalchik, 37-a I. Armand street
    ahmedenes@mail.ru<\/p>\n\n\n\n

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    Formal genome model of a general artificial intelligence agent based on multi-agent neurocognitive architectures M.I. Anchekov, A.Z. Apshev, K.Ch. Bzhikhatlov, S.A. Kankulov,Z.V. Nagoev, O.V. Nagoeva, I.A. Pshenokova, A.A. Khamov, A.Z. Enes Upload the full text Abstract: The relevance of the research is determined by the need to develop and programmatically implement artificial general intelligence agents […]<\/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-9730","page","type-page","status-publish","hentry"],"yoast_head":"\n25.5.1 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\/25-5-1-en\/\" \/>\n<meta property=\"og:locale\" content=\"ru_RU\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"25.5.1 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=\"Formal genome model of a general artificial intelligence agent based on multi-agent neurocognitive architectures M.I. 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