Concept for collaborative system for automatic virtual prototyping of neuroprostheses based on epistemological algorithms for learning intelligent software agents

Z.V. Nagoev, O.V. Nagoeva

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Abstract: The development and implementation of neuroprosthetics is urgently needed to improve the functionality and effectiveness of technical rehabilitation tools for patients with lost or partially damaged organs, as well as to enhance their quality of life. The development of prosthetics, in its broadest sense, is linked to the need to address a range of challenges related to ensuring the structural and functional compatibility of complex artificial hardware and software devices with the tissues and systems of biological organisms.
Aim. The study is to develop and substantiate the concept of a system for autonomous collaborative design of neurocompatible prostheses.
Materials and methods. The object of this study is a methodology for creating an infrastructure for collaborative automated design and prototyping of neurocompatible prostheses. The subject of the study is the feasibility of developing a system for collaborative design and prototyping of neurocompatible prostheses based on intelligent software neurocognitive agents.
Results. A concept for autonomous collaborative design systems for neurocompatible prostheses has been developed and validated. Key requirements for intelligent control systems for neurocompatible prostheses and principles for their creation based on collaborative human-machine systems for autonomous design and prototyping have been developed. The feasibility of creating and developing an architecture for a collaborative autonomous design system for neurocompatible prostheses based on intelligent software neurocognitive agents has been substantiated.

Keywords: neurocompatible prostheses, collaborative design systems, autonomous design, virtual prototyping, intelligent software agents, multi-agent neurocognitive architectures

For citation. Nagoev Z.V., Nagoeva O.V. Concept for collaborative system for automatic virtual prototyping of neuroprostheses based on epistemological algorithms for learning intelligent software agents. News of the Kabardino-Balkarian Scientific Center of RAS. 2025. Vol. 27. No. 5. Pp. 80–97. DOI: 10.35330/1991-6639-2025-27-5-80-97

References

1. Nagoev Z.V. Intellektika, ili Myshleniye v zhivykh i iskusstvennykh sistemakh [Intellectics, or Thinking in Living and Artificial Systems]. Nalchik: Publishing House of the KabardinoBalkarian Scientific Center of the Russian Academy of Sciences, 2013. 235 p. (In Russian)
2. Nagoev Z.V., Nagoeva O.V. Obosnovaniye simvolov i mul’tiagentnyye neyrokognitivnyye modeli semantiki yestestvennogo yazyka [Symbol Grounding and Multi-Agent Neurocognitive Models of Natural Language Semantics]. Nalchik: Izdatel’stvo KBNTS RAN, 2022. 150 p. (In Russian)
3. Kwok R. Neuroprosthetics: Once more, with feeling. Nature. 2013. Vol. 497. Pp. 176–178.
4. Kravchenko S.V. Development of a prototyping system for neuroprostheses based on a hybrid hardware-software implementation of spiking neural networks. Bulletin of Cybernetics. No. 22(4). Pp. 26–32. DOI: 10.35266/1999-7604-2023-4-4. (In Russian)
5. Abutalipov R.N., Zammoev A.U., Nagoev Z.V. Bionanorobotics: conceptualization, problems and research tasks. News of the Kabardino-Balkarian Scientific Center of RAS. 2016.
   No. 6(74). Pp. 11–17. EDN: XRUYRN. (In Russian)
6. Abutalipov R.N., Zammoev A.U. The problem of developing the theoretical foundations for the design and prototyping of devices and systems of bionanorobotics in cyber-physical systems and environments. News of the Kabardino-Balkarian Scientific Center of RAS. 2022. No. 6(110). Pp. 28–38. DOI: 10.35330/1991-6639-2022-6-110-28-38. (In Russian)
7. Clausen J., Fetz E., Donoghue J. et al. Help, hope and hype: Ethical dimensions of neuroprosthetics. Science. 2017. Vol. 356. Pp. 1338–1339. DOI: 10.1126/science.aam7731
8. Nagoev Z.V. Basic principles of neurocognitive modeling of consciousness of an agent of universal artificial intelligence. News of the Kabardino-Balkarian Scientific Center of RAS. 2025. Vol. 27. No. 1. Pp. 152–170. DOI: 10.35330/1991-6639-2025-27-1-152-170. (In Russian)
9. Nagoev Z.V. Genomic control of agent morphogenesis in a virtual “physically correct” environment. Cybernetics and Systems Analysis. 2008. No. 2.
10. Nagoev Z.V., Kudaev V.Ch., Oshkhunov M.M., Pshenokova I.A. Ontoneuromorphogenetic modeling of virtual proto types in integrated CADs on a basis of multiagent knowledge and bioinspired algorithms. News of the Kabardino-Balkarian Scientific Center of RAS. 2013. No. 6-1(56). Pp. 46–53. EDN: RPXLRL. (In Russian)
11. Kudaev A.Yu., Lezhebokov A.A., Nagoev Z.V. Virtual prototyping in integrated CADs of engineering and electronics based on the ontoneuromorphogenetic modeling. Izvestiya SFedU. Engineering Sciences. 2013. No. 7(144). Pp. 29–35. EDN: QOUCHP. (In Russian)
12. Nagoev Z., Nagoeva O., Anchokov M. et al. The symbol grounding problem in the system of general artificial intelligence based on multi-agent neurocognitive architecture. Cognitive Systems Research. 2023. Vol. 79. Pp. 71–84. DOI: 10.1016/j.cogsys.2023.01.002
13. Nagoev Z., Pshenokova I., Nagoeva O., Sundukov Z. Learning algorithm for an intelligent decision making system based on multi-agent neurocognitive architectures. Cognitive Systems Research. 2021. Vol. 66. Pp. 82–88. DOI: 10.1016/j.cogsys.2020.10.015
14. 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 to
    automatically replenish ontologies. News of the Kabardino-Balkarian Scientific Center of RAS. No. 6(116). Pp. 226–234. DOI: 10.35330/1991-6639-2023-6-116-226-234. (In Russian)
15. Nagoev Z.V. Ontoneuromorphogenetic modeling. News of the Kabardino-Balkarian Scientific Center of RAS. 2013. No. 4(54). Pp. 56–63. EDN: QZTFLN. (In Russian)

Information about the authors

Zalimkhan V. Nagoev, Candidate of Technical Sciences, General Director of the Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences;
2 Balkarov street, Nalchik, 360010, Russia;
Leading Researcher of the Department “Multi-Agent Systems”, Institute of Computer Science and Problems of Regional Management – branch of 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, Researcher of the Department “Multiagent Systems”, Institute of Computer Science and Problems of Regional Management – branch of 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