Analysis of computational complexity of federated algorithms for neurocognitive control of imitation phenogenetic models of plants
M.A. Abazokov, M.I. Anchekov, K.Ch. Bzhikhatlov, Zh.Kh. Kurashev,
Z.V. Nagoev, O.V. Nagoeva, A.A. Unagasov, A.A. Khamov
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Abstract. The aim of the study is to develop a methodology for creating hybrids of economically useful plants with a given set of phenotypic properties based on the use of universal artificial intelligence methods for managing federated simulation models of vegetation. The main objective of this work is to analyze the computational complexity of the main algorithms for the functioning and training of neurocognitive systems for managing federated simulation models of plant vegetation using computers of various types. The paper presents the results of estimating the execution time of the dispatching cycle in a federated system for imitation modeling of plant phenogenetic dynamics on a sequential and parallel computer.
Keywords: universal artificial intelligence, multi-agent systems, neurocognitive control, plant breeding, gene expression, computational complexity analysis, federated algorithms
For citation. Abazokov M.A., Anchekov M.I., Bzhikhatlov K.Ch., Kurashev Zh.Kh., Nagoev Z.V., Nagoeva O.V., Unagasov A.A., Khamov A.A. Analysis of computational complexity of federated algorithms for neurocognitive control of imitation phenogenetic models of plants. News of the Kabardino-Balkarian Scientific Center of RAS.2024. Vol. 26. No. 5. Pp. 107–128. DOI: 10.35330/1991-6639-2024-26-5-107-128
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Information about the authors
Mukhamed A. Abazokov, Junior Researcher, Laboratory of “Neurocognitive Autonomous Intelligent Systems”, Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences;
360002, Russia, Nalchik, 2 Balkarov street;
abazokov1997@mail.ru, ORCID: https://orcid.org/0000-0002-8710-1562, SPIN-code: 5167-5962
Murat I. Anchekov, Researcher, Laboratory of “Molecular selection and biotechnology”, KabardinoBalkarian 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, SPIN-code: 3299-0927
Kantemir Ch. Bzhikhatlov, Candidate of Physical and Mathematical Sciences, Head of the Laboratory of “Neurocognitive Autonomous Intelligent Systems”, 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, SPIN-code: 9551-5494
Zhiraslan Kh. Kurashev, Head of the Laboratory of “Molecular Breeding and Biotechnology”, Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences;
360000, Russia, Nalchik, 224 Kirov street;
ORCID: https://orcid.org/0000-0001-9442-6122, SPIN-code: 8549-2620
Zalimkhan V. Nagoev, Candidate of Technical Sciences, General Director of the KabardinoBalkarian 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, SPIN-code: 6279-5857
Olga V. Nagoeva, Researcher, Department of “Multiagent Systems”, Institute of Computer Science and Problems of Regional Management – 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, SPIN-code: 9478-3325
Alim A. Unagasov, Junior Researcher, Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences;
360000, Russia, Nalchik, 37-a I. Armand street;
alim.unagasov@mail.ru, ORCID: https://orcid.org/0000-0003-3828-7468
Anzor A. Khamov, Junior Researcher, Laboratory of “Molecular Breeding and Biotechnology”, 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