{"id":6065,"date":"2026-01-21T12:13:04","date_gmt":"2026-01-21T12:13:04","guid":{"rendered":"https:\/\/izvestiyakbncran.ru\/?page_id=6065"},"modified":"2026-04-13T13:13:36","modified_gmt":"2026-04-13T12:13:36","slug":"27-6-15-en","status":"publish","type":"page","link":"https:\/\/izvestiyakbncran.ru\/index.php\/en\/27-6-15-en\/","title":{"rendered":"27.6.15 En"},"content":{"rendered":"\n

\u201cWhat does the brain do?\u201d, or Solving a priori undefined problems based on an autonomous agent behavior in real environment<\/strong><\/h1>\n\n\n\n

Z.V. Nagoev, O.V. Nagoeva<\/strong><\/p>\n\n\n\n

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Upload the full text<\/strong><\/strong><\/p>\n\n\n\n

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Abstract<\/strong>.<\/strong> <\/em>The relevance of the work is determined by the need to develop theoretical foundations for the creation of universal artificial intelligence systems.
Aim<\/strong>. This work is to create a conceptual model of the systemic essence of the brain.
Research methods<\/strong>. Of fundamental importance is that both ontology meta-matching technique and problem-solving algorithms synthesize points and segments along an agent’s movement in a behavioral space. This means that ontologization, identification, and solution of all problems encountered by the agent in the real environment during its existence are accomplished through the synthesis and implementation of the agent’s behavior in that environment.
Results<\/strong>. A hypothesis about the systematic target function of the brain has been formulated, and a computational model of the basic processes underlying its operation has been developed, based on the analogy of designing a neurocognitive system to control the behavior of an autonomous agent in a real-world environment. A concept of an agent’s existence as a trajectory in its behavioral space was proposed, which is a mathematical abstraction of the state space of the «agent \u2013 environment \u2013 observer» system. A concept for adapting agents to real-world conditions has been proposed, based on brain-implemented meta-algorithms for ontologization and algorithms for identifying and solving a priori undefined problems, grounded on a metaphor for designing an autonomous synthesis of the agent’s trajectory in behavioral space.
Conclusion<\/strong>. The developed concepts support the idea of ontologization, identification, and problemsolving by an agent in a real-world environment as processes of autonomous behavior synthesis, which provides a theoretical foundation for the development of universal artificial intelligence systems.<\/p>\n\n\n\n

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Keywords<\/strong><\/em><\/strong>:<\/em> general artificial intelligence, human brain, thought models, multi-agent systems, neurocognitive architectures, solving a priori undefined problems<\/p>\n\n\n\n

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For citation<\/strong>.<\/strong> Nagoev Z.V., Nagoeva O.V. \u201cWhat does the brain do?\u201d, or Solving a priori undefined problems based on an autonomous agent behavior in real environment. News of the Kabardino-Balkarian Scientific Center of RAS<\/em>. Vol. 27. No. 6. Pp. 172\u2013185. DOI: 10.35330\/1991-6639-2025-27-6-172-185<\/p>\n\n\n\n

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R<\/strong>eferences<\/summary>\n
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  1. Minsky M. Steps toward Artificial Intelligence. Proceedings of the IRE. 1961. Vol. 49. No. 1. Pp. 8\u201330.<\/li>\n\n\n\n
  2. Minsky M. Vychisleniya i avtomaty [Computations and Automata]. Moscow: Mir, 1971. (In Russian)<\/li>\n\n\n\n
  3. Nagoev Z.V. Basic principles of neurocognitive modeling of consciousness of a universal artificial intelligence agent. News of the Kabardino-Balkarian Scientific Center of RAS. 2025. Vol. 27. No. 1. Pp. 152\u2013170. DOI: 10.35330\/1991-6639-2025-27-1-152-170. (In Russian)<\/li>\n\n\n\n
  4. Nagoev Z.V., Nagoeva O.V. Obosnovaniye simvolov i mul’tiagentnyye neyrokognitivnyye modeli semantiki yestestvennogo yazyka [Justification of Symbols and Multi-Agent Neurocognitive Models of Natural Language Semantics]. Nalchik: Izdatel’stvo KBNTS RAN, 2022. 150 p. (In Russian)<\/li>\n\n\n\n
  5. Nagoev Z.V. Multi-agent existential mappings and functions. News of the KabardinoBalkarian Scientific Center of RAS. 2013. No. 4(54). Pp. 63\u201371. EDN: QZTFLX. (In Russian)<\/li>\n\n\n\n
  6. Russell S., Norvig P. Artificial Intelligence: A Modern Approach (AIMA). 2nd ed. Moscow: Williams, 2007. 1424 p.<\/li>\n\n\n\n
  7. Nagoev Z.V. Intellektika, ili myshleniye v zhivykh i iskusstvennykh sistemakh [Intellectics, or thinking in living and artificial systems]. Nalchik: Izdatel’stvo KBNTS RAN, 2013. 232 p.
    (In Russian)<\/li>\n\n\n\n
  8. Nagoev Z.V. Ontoneuromorphogenetic modeling. News of the Kabardino-Balkarian Scientific Center of RAS. 2013. No. 4(54). Pp. 56\u201363. EDN: QZTFLN. (In Russian)<\/li>\n\n\n\n
  9. Nagoev Z.V., Kudayev V.Ch., Oshkhunov M.M., Pshenokova I.A. Ontoneuromorphogenetic modeling of virtual prototypes in integrated cad systems based on multi-agent knowledge and bioinspired algorithms. News of the Kabardino-Balkarian Scientific Center of RAS. 2013. No. 6-1(56). Pp. 46\u201353. EDN: RPXLRL. (In Russian)<\/li>\n\n\n\n
  10. Nagoev Z.V., Pshenokova I.A., Nagoeva O.V. et al. Simulation model of a neurocognitive control system for an autonomous software agent performing cooperative behavior for the purpose of automatic ontology replenishment. News of the Kabardino-Balkarian Scientific Center of RAS. 2023. No. 6(116). Pp. 226\u2013234. DOI: 10.35330\/1991-6639-2023-6-116-226-234. (In Russian)<\/li>\n\n\n\n
  11. Nagoev Z.V., Anchekov M.I., Bzhikhatlov K.Ch. et al. Ontoepisociophylogenetic development of general artificial intelligence systems based on multi-agent neurocognitive architectures. News of the Kabardino-Balkarian Scientific Center of RAS. 2022. No. 6(110). Pp. 61\u201375. DOI: 10.35330\/1991-6639-2022-6-110-61-75. (In Russian)<\/li>\n\n\n\n
  12. Apshev A.Z., Atalikov B.A., Kankulov S.A. et al. Ontophylogenetic algorithms for synthesizing phenotypes of intelligent software agents for application in multigenerational optimization problems of control neurocognitive architectures. News of the Kabardino-Balkarian Scientific Center of RAS. 2022. No. 6(110). Pp. 76\u201391. DOI: 10.35330\/1991-6639-2022-6-110-76-91. (In Russian)<\/li>\n\n\n\n
  13. Nagoev Z.V. Multiagent recursive cognitive architecture. Biologically Inspired Cognitive Architectures 2012. Proceedings of the third annual meeting of the BICA Society, in Advances in Intelligent Systems and Computing series, Springer, 2012. Pp. 247\u2013248.<\/li>\n\n\n\n
  14. Bzhikhatlov K.Ch., Pshenokova I.A., Zammoev A.U. Architecture and algorithm of the information security system for autonomous intelligent systems and complexes. Information
    Society. 2025. No. 1. Pp. 118\u2013127. DOI: 10.52605\/16059921_2025_01_118<\/li>\n\n\n\n
  15. Pshenokova I., Anchokov M., Kankulov S. et al. Simulation model of the decentralized control of autonomous software agents\u2019 teams and mobile robots. In: Samsonovich A.V., Liu T. (eds) Biologically Inspired Cognitive Architectures 2024. BICA. Studies in Computational Intelligence. Vol. 477. Pp. 1\u20138. DOI: 10.1007\/978-3-031-76516-2_31<\/li>\n<\/ol>\n<\/details>\n\n\n\n
    Information about the author<\/strong>s<\/summary>\n
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    Zalimkhan V. Nagoev<\/strong>, Candidate of Technical Sciences, General Director of the Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences;
    Leading Researcher of the Department \u201cMulti-Agent Systems\u201d, Institute of Computer Science and Problems of Regional Management \u2013 branch of the Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences;
    37-a, I. Armand street, Nalchik, 360000, Russia;
    zaliman@mail.ru, ORCID: https:\/\/orcid.org\/0000-0001-9549-1823, SPIN-code: 6279-5857
    Olga V. Nagoeva<\/strong>, Researcher, Multiagent Systems Department, Institute of Computer Science and Problems of Regional Management \u2013 branch of the Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences;
    37-a, I. Armand street, Nalchik, 360000, Russia;
    nagoeva_o@mail.ru, ORCID: https:\/\/orcid.org\/0000-0003-2341-7960<\/p>\n\n\n\n

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    \u201cWhat does the brain do?\u201d, or Solving a priori undefined problems based on an autonomous agent behavior in real environment Z.V. Nagoev, O.V. Nagoeva Upload the full text Abstract. The relevance of the work is determined by the need to develop theoretical foundations for the creation of universal artificial intelligence systems.Aim. This work is to […]<\/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-6065","page","type-page","status-publish","hentry"],"yoast_head":"\n27.6.15 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\/27-6-15-en\/\" \/>\n<meta property=\"og:locale\" content=\"ru_RU\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"27.6.15 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=\"\u201cWhat does the brain do?\u201d, or Solving a priori undefined problems based on an autonomous agent behavior in real environment Z.V. 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