{"id":2192,"date":"2025-05-13T11:48:21","date_gmt":"2025-05-13T10:48:21","guid":{"rendered":"http:\/\/newskbncran.ru\/?page_id=2192"},"modified":"2026-03-30T15:57:04","modified_gmt":"2026-03-30T14:57:04","slug":"26-5-11-en","status":"publish","type":"page","link":"https:\/\/izvestiyakbncran.ru\/index.php\/en\/26-5-11-en\/","title":{"rendered":"26.5.11 en"},"content":{"rendered":"\n<h4 class=\"wp-block-heading has-lora-font-family\" style=\"line-height:1.4\"><strong>Multi-agent neurocognitive model of a control system for the coordinated behavior of an autonomous agents\u2019 collective<\/strong><\/h4>\n\n\n\n<p class=\"has-foreground-color has-text-color has-link-color has-lora-font-family has-medium-font-size wp-elements-4b2b09d5cfbe24f2d6fcc47b75c1ba91\"><strong><strong>I.A. Pshenokova, S.A. Kankulov, B.A. Atalikov, A.Z. Enes<\/strong><\/strong><\/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-24a27e19 wp-block-group-is-layout-flex\" style=\"margin-top:0;margin-bottom:0;padding-top:0;padding-bottom:0\">\n<p class=\"has-text-color has-link-color has-medium-font-size wp-elements-4a9ce8c8f4eb81997c58bba471cf3274\" style=\"color:#5b1919;text-decoration:underline\"><strong>Upload the full text<\/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\/2024\/11\/pshen-11.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-ae840b2df68d0132c22b82f517b9f302\" style=\"line-height:1.4\"><strong><em>Abstract<\/em><\/strong><em>.<\/em><strong> <\/strong>The main goal of the research is to develop a decentralized system for controlling the coordinated behavior of a team of autonomous agents based on a multi-agent neurocognitive architecture. The task of developing a decentralized control system is solved based on the self-organization of multi-agent neurocognitive architectures of autonomous agents as part of a single cognitive architecture and the formation of a common mission graph. The vertices of the graph will be complex states that represent the union of the states of all agents in the group, and the arcs will be the sets of actions of the group members leading from one complex state to another. The presented model will allow to create decentralized, flexible and scalable control systems for a group of intelligent agents to solve complex problems and can be used in robotics.<\/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-7f1a65f204cca626749d447ddc3529a3\" style=\"line-height:1.4\"><strong><em>Keywords<\/em><\/strong><em>:<\/em> control system, multi-agent systems, decentralized systems, intelligent agent<\/p>\n\n\n\n<p class=\"has-foreground-color has-text-color has-link-color has-lora-font-family wp-elements-5a817d35c0b528e0f6c4ffb074d2f0dd\" style=\"font-size:12px;line-height:1.4\"><strong>For citation<\/strong>. Pshenokova I.A., Kankulov S.A., Atalikov B.A., Enes A.Z. Multi-agent neurocognitive model of a control system for the coordinated behavior of an autonomous agents\u2019 collective. <em>News of the Kabardino-Balkarian Scientific Center of RAS.<\/em>2024. Vol. 26. No. 5. Pp. 138\u2013146. DOI: 10.35330<strong>\/<\/strong>1991-6639-2024-26-5-138-146<\/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-3e2eb7ee837ceacd4a2064557acf7b70 is-layout-flow wp-block-details-is-layout-flow\"><summary><strong>References<\/strong><\/summary>\n<ol class=\"wp-block-list\">\n<li>Li Q., Gama F., Ribeiro A., Prorok A. Graph neural networks for decentralized multi-robot path planning. <em>IEEE\/RSJ international conference on intelligent robots and systems (IROS)<\/em>. Pp. 11785\u201311792. DOI: 10.1109\/iros45743.2020.9341668<\/li>\n\n\n\n<li>Desaraju V., How J. Decentralized path planning for multi-agent teams with complex constraints. <em>Autonomous Robots<\/em>, 2012. No. 32(4). Pp. 385\u2013403. DOI: 10.1007\/s10514-012-9275-2<\/li>\n\n\n\n<li>Patwardhan A., Murai R., Davison A.J. Distributing collaborative multi-robot planning with gaussian belief propagation.<em> IEEE Robotics and Automation Letters<\/em>, 2023. No. 8(2). Pp. 552\u2013559. DOI: 10.1109\/LRA.2022.3227858<\/li>\n\n\n\n<li>Sharon G., Stern, R., Felner A., Sturtevant N.R. Conflict-based search for optimal multiagent pathfinding. Artificial Intelligence, 2012. 219. Pp. 40\u201366. DOI: 10.1016\/j.artint.2014.11.006<\/li>\n\n\n\n<li>Gulati R., Wohlgezogen F., Zhelyazkov P. The two facets of collaboration: Cooperation and coordination in strategic alliances. <em>Academy of Management Annals<\/em>. 2012. No. 6(1). Pp. 531\u2013583.<\/li>\n\n\n\n<li>Lumineau F., Wang W., Schilke O. Blockchain governance \u2013 A new way of organizing collaborations? <em>Organization Science.<\/em> 2021. No. 32(2). Pp. 500\u2013521. DOI: 10.1287\/orsc.2020.1379<\/li>\n\n\n\n<li>Fragapane G., de Koster R., Sgarbossa F., Strandhagen J. Planning and control of autonomous mobile robots for intralogistics: Literature review and research agenda. <em>European Journal of Operational Research<\/em>. 2021. Vol. 294 (2). Pp. 405\u2013426. DOI: 10.1016\/j.ejor.2021.01.019<\/li>\n\n\n\n<li>Turner J., Meng G., Schaefer G. et al. Distributed task rescheduling with time constraints for the optimization of total task allocations in a multirobot system. <em>IEEE transactions on cybernetics<\/em>. 2017. 48(9). Pp. 2583\u20132597. DOI: 10.1109\/TCYB.2017.2743164<\/li>\n\n\n\n<li>Mkiramweni M.E. et al. A survey of game theory in unmanned aerial vehicles communications. <em>IEEE Communications Surveys &amp; Tutorials<\/em>. 2019. 21(4). Pp. 3386\u20133416.<\/li>\n\n\n\n<li>Zhu X., Vanegas F., Gonzalez F. Decentralised multi-UAV cooperative searching multitarget in cluttered and GPS-denied environments. <em>2022 IEEE Aerospace Conference (AERO)<\/em>. <em>IEEE,<\/em> 2022. Pp. 1\u201310.<\/li>\n\n\n\n<li>Tkach I., Blackwell T. On the Optimization of systems using AI metaheuristics and evolutionary algorithms. International Conference on Production Research. Cham: Springer International Publishing, 2021. Pp. 253\u2013271.<\/li>\n\n\n\n<li>Keskin M.O., Cant\u00fcrk F., Eran C. et al. Decentralized multi-agent path finding framework and strategies based on automated negotiation. <em>Auton Agent Multi-Agent Syst<\/em>. Vol. 38. No. 10. DOI: 10.1007\/s10458-024-09639-8<\/li>\n\n\n\n<li>Pshenokova I.A., Apshev A.Z. Energy exchange model among agneurons as part of multiagent neurocognitive architecture. <em>News of the Kabardino-Balkarian Scientific Center of RAS<\/em>. No. 5(115). Pp. 32\u201340. DOI: 10.35330\/1991-6639-2023-5-115-32-40. (In Russian)<\/li>\n\n\n\n<li>Nagoev Z., Pshenokova I., Nagoeva O., Kankulov S. Situational analysis model in an intelligent system based on multi-agent neurocognitive architectures.<em> Journal of Physics: Conference Series<\/em>. 2021. Vol. 2131. Article No. 022103. DOI: 10.1088\/1742-6596\/2131\/2\/022103<\/li>\n\n\n\n<li>Pshenokova I., Bzhikhatlov K., Kankulov S. et al. Simulation model of the neurocognitive system controlling an intellectual agent displaying exploratory behavior in the real world. In: Alexei V. Samsonovich. Tingting Liu Proceedings of the 14th Annual Meeting of the BICA Society. BICA 2023. <em>Studies in Computational Intelligence (SCI)<\/em>. Vol. 1130. DOI: 10.1007\/978-3-031-50381-8_76<\/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-c0bc64978eb8dcc1d56bab64a2e305f9 is-layout-flow wp-block-details-is-layout-flow\"><summary><strong>Information about the authors<\/strong><\/summary>\n<p style=\"margin-top:var(--wp--preset--spacing--20);margin-bottom:var(--wp--preset--spacing--20)\"><strong>Inna A. Pshenokova<\/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, SPIN-\u043a\u043e\u0434: 3535-2963<br><strong>Sultan Akh. Kankulov<\/strong>, Junior Researcher, Department of \u201cNeurocognitive Autonomous Intelligent Systems\u201d, Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences;<br>360000, Russia, Nalchik, 37-a I. Armand street;<br>skankulov@mail.ru, ORCID: https:\/\/orcid.org\/0000-0002-2996-7376, SPIN-\u043a\u043e\u0434: 4342-5381<br><strong>Boris A. Atalikov<\/strong>, Junior Researcher, Laboratory of \u201cNeurocognitive Autonomous Intelligent Systems\u201d, Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences;<br>360000, Russia, Nalchik, 37-a I. Armand street;<br>atalikov10@gmail.com<br><strong>Ahmed Z. Enes<\/strong>, Junior Researcher, Laboratory of \u201cNeurocognitive Autonomous Intelligent Systems\u201d, 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, SPIN-\u043a\u043e\u0434: 3643-1808<\/p>\n\n\n\n<p><\/p>\n<\/details>\n","protected":false},"excerpt":{"rendered":"<p>Multi-agent neurocognitive model of a control system for the coordinated behavior of an autonomous agents\u2019 collective I.A. Pshenokova, S.A. Kankulov, B.A. Atalikov, A.Z. Enes Upload the full text Abstract. The main goal of the research is to develop a decentralized system for controlling the coordinated behavior of a team of autonomous agents based on a [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-2192","page","type-page","status-publish","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>26.5.11 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\/26-5-11-en\/\" \/>\n<meta property=\"og:locale\" content=\"ru_RU\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"26.5.11 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=\"Multi-agent neurocognitive model of a control system for the coordinated behavior of an autonomous agents\u2019 collective I.A. 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Pshenokova, S.A. Kankulov, B.A. Atalikov, A.Z. Enes Upload the full text Abstract. 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