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Publications in Math-Net.Ru |
Citations |
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2023 |
| 1. |
Z. V. Nagoev, I. A. Pshenokova, M. I. Anchekov, K. Ch. Bzhikhatlov, B. A. Atalikov, S. A. Kankulov, A. Z. Enes, “Classification and conditions of application of algorithms
for automatic ontologization of the state space of a general artificial
intelligence agent under the control of neurocognitive architecture”, News of the Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences, 2023, no. 6, 210–225   |
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| 2. |
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, “Formal genome model of a general artificial intelligence agent based
on multi-agent neurocognitive architectures”, News of the Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences, 2023, no. 5, 11–24 |
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2022 |
| 3. |
A. Z. Apshev, B. A. Atalikov, S. A. Kankulov, D. A. Malyshev, Z. A. Sundukov, A. Z. Enes, “Ontophylogenetic algorithms for the synthesis of intellectual phenotypes
of software agents for use in tasks of multigenerational optimization
of control neurocognitive architectures”, News of the Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences, 2022, no. 6, 76–91 |
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| 4. |
M. I. Anchekov, K. Ch. Bzhikhatlov, S. A. Kankulov, Z. V. Nagoev, O. V. Nagoeva, I. A. Pshenokova, “A multi-agent algorithm for substantiating
the symbols of a conventional language based on situational development
of neurocognitive architecture”, News of the Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences, 2022, no. 6, 48–60 |
| 5. |
A. M. Ksalov, K. Ch. Bzhikhatlov, S. A. Kankulov, B. A. Atalikov, A. Z. Enes, “Data visualization system for intelligent expert system
of active plant protection”, News of the Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences, 2022, no. 2, 22–30 |
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2021 |
| 6. |
Z. V. Nagoev, I. A. Pshenokova, K. Ch. Bzhikhatlov, S. A. Kankulov, “Simulation model of an intelligent control system
for the agricultural grip manipulator
based on the multi-agent neurocognitive
architectures training”, News of the Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences, 2021, no. 4, 28–37 |
| 7. |
Z. V. Nagoev, I. A. Pshenokova, S. A. Kankulov, B. A. Atalikov, A. A. Airan, “Multi-agent search formal model for an
intelligent agent optimal behavior plan based
on distributed neurocognitive
architectures self-organization”, News of the Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences, 2021, no. 3, 21–31 |
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2020 |
| 8. |
Z. V. Nagoev, K. Ch. Bzhikhatlov, O. V. Nagoeva, Z. A. Sundukov, S. A. Kankulov, “Autonomous formation of a user model based
on digital footprint data in the internet space based
on training multi-agent neurocognitive architectures”, News of the Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences, 2020, no. 6, 52–67 |
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