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Publications in Math-Net.Ru |
Citations |
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2023 |
| 1. |
Z. V. Nagoev, I. A. Pshenokova, O. V. Nagoeva, M. I. Anchekov, A. Z. Enes, “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 the Russian Academy of Sciences, 2023, no. 6, 226–234   |
| 2. |
Z. V. Nagoev, O. V. Nagoeva, D. G. Makoeva, I. A. Gurtueva, “Multi-agent neurocognitive algorithm for controlling the reference
of speech events of communication of a general artificial intelligence agent
in a situation of synchronous multiple dialogues”, News of the Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences, 2023, no. 6, 193–209 |
| 3. |
K. Ch. Bzhikhatlov, I. A. Pshenokova, O. V. Nagoeva, “Cooperative interaction of participants in a heterogeneous team
of autonomous agents using neurocognitive models
of coordinated behavior”, News of the Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences, 2023, no. 6, 132–141 |
| 4. |
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 |
| 5. |
M. I. Anchekov, K. Ch. Bzhikhatlov, Z. V. Nagoev, O. V. Nagoeva, I. A. Pshenokova, “Ontoepisociophylogenetic development
of artificial general intelligence systems
based on multi-agent neurocognitive architectures”, News of the Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences, 2022, no. 6, 61–75 |
1
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| 6. |
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 |
| 7. |
I. A. Pshenokova, O. V. Nagoeva, A. Z. Apshev, A. Z. Enes, “Formation of dynamic cause-and-effect relationships when controlling
the behavior of an intelligent agent based
on the multi-agent neurocognitive architectures formalism”, News of the Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences, 2022, no. 5, 73–80 |
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2021 |
| 8. |
Z. V. Nagoev, I. A. Pshenokova, O. V. Nagoeva, “Automatic reconstruction of the character
and temperament of users based on multi-agent
training of neurocognitive models of the conscious
and unconscious according to data on user
behavior in the internet”, News of the Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences, 2021, no. 6, 66–77 |
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2020 |
| 9. |
Z. V. Nagoev, K. Ch. Bzhikhatlov, I. A. Pshenokova, O. V. Nagoeva, B. A. Atalikov, N. A. Chechenova, D. A. Malyshev, “Autonomous formation of spatial ontologies
in the intelligent decision-making system of a mobile agricultural robot based on the self-organization
of multi-agent neurocognitive architectures”, News of the Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences, 2020, no. 6, 68–79 |
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| 10. |
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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| 11. |
I. A. Pshenokova, O. V. Nagoeva, I. A. Gurtueva, A. A. Airan, “Learning algorithm for an intelligent
decision making system based on multi-agent
neurocognitive architectures”, News of the Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences, 2020, no. 3, 23–31 |
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2019 |
| 12. |
O. V. Nagoeva, M. I. Anchekov, “Development of a software model for a robot combine control system”, News of the Kabardin-Balkar scientific center of RAS, 2019, no. 3, 15–22 |
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| 13. |
Z. V. Nagoev, O. V. Nagoeva, I. A. Pshenokova, “Multi-agent neurocognitive models of semantics of spatial localization of events”, News of the Kabardin-Balkar scientific center of RAS, 2019, no. 2, 11–23 |
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| 14. |
I. A. Pshenokova, O. V. Nagoeva, Z. A. Sundukov, V. A. Denisenko, “Architecture of multi-agent neurocognitive system providing semantic representation of multimodal images in technology of machine vision”, News of the Kabardin-Balkar scientific center of RAS, 2019, no. 1, 16–22 |
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2018 |
| 15. |
A. M. Tolstykh, B. I. Shkalenko, Yu. A. Kravchenko, O. V. Nagoeva, “Prospects of development of methods of intellectual
data analysis on the basis of virtual reality model”, News of the Kabardin-Balkar scientific center of RAS, 2018, no. 6-3, 146–151 |
1
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| 16. |
Z. V. Nagoev, O. V. Nagoeva, “Simulation of semantics of phrases with attributive adjectives on the basis of the recursive multiagent cognitive architecture”, News of the Kabardin-Balkar scientific center of RAS, 2018, no. 3, 11–20 |
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2017 |
| 17. |
I. A. Pshenokova, M. I. Anchekov, V. A. Denisenko, O. V. Nagoeva, D. G. Makoeva, Z. A. Sundukov, “Complexation of multi-modal data
in intelligent habitat based on multi-agent
recursive cognitive architectures”, News of the Kabardin-Balkar scientific center of RAS, 2017, no. 6-2, 197–202 |
1
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| 18. |
Z. V. Nagoev, O. V. Nagoeva, I. A. Pshenokova, “A formal model of semantics of natural language utterances on the basis of multiagent recursive cognitive architectures”, News of the Kabardin-Balkar scientific center of RAS, 2017, no. 4, 19–31 |
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2015 |
| 19. |
I. A. Pshenokova, V. A. Denisenko, O. V. Nagoeva, D. G. Tokmakova, Z. A. Sundukov, “Knowledge representation in artificial intelligence
systems based on the principles
of ontoneuromorphogenesis
and multi-agent modeling”, News of the Kabardin-Balkar scientific center of RAS, 2015, no. 6-2, 158–165 |
1
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| 20. |
O. V. Nagoeva, D. G. Makoeva, R. A. Shankov, “Paradigmatic relations of language units
modeling based on multi-agent
recursive architecture”, News of the Kabardin-Balkar scientific center of RAS, 2015, no. 6-2, 153–157 |
| 21. |
Z. V. Nagoev, O. V. Nagoeva, “Extraction of knowledge from multimodal flows
of unstructured data on the basis of self-organization
of multi-agent cognitive architecture
of the mobile robot”, News of the Kabardin-Balkar scientific center of RAS, 2015, no. 6-2, 145–152 |
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| 22. |
Yu. A. Kravchenko, D. Yu. Kravchenko, E. V. Kuliev, O. V. Nagoeva, I. A. Pshenokova, “Knowledge management architecture
in intelligent transport systems”, News of the Kabardin-Balkar scientific center of RAS, 2015, no. 6-2, 93–99 |
| 23. |
M. I. Anchekov, Yu. Kh. Khamukov, O. V. Nagoeva, D. Y. Zaporozhets, A. A. Lezhebokov, “Multi-agent genetic algorithm for solving knowledge extraction problem”, News of the Kabardin-Balkar scientific center of RAS, 2015, no. 6-2, 12–19 |
| 24. |
Z. V. Nagoev, O. V. Nagoeva, V. A. Denisenko, A. M. Ksalov, Yu. Kh. Khamukov, “Epistemological models
and systems of the mobile robotics”, News of the Kabardin-Balkar scientific center of RAS, 2015, no. 5, 31–37 |
| 25. |
M. I. Anchekov, V. V. Bova, O. V. Nagoeva, A. A. Novikov, I. A. Pshenokova, “Evolutionary approach to creating a neural network
model of collective decisions of intellectual tasks”, News of the Kabardin-Balkar scientific center of RAS, 2015, no. 5, 24–30 |
2
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| 26. |
A. N. Dukkardt, M. I. Anchekov, Z. V. Nagoev, A. U. Zammoev, O. V. Nagoeva, Yu. Kh. Khamukov, “Task allocation in distributed artificial intelligence using collective behavior models”, News of the Kabardin-Balkar scientific center of RAS, 2015, no. 1, 16–22 |
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| 27. |
M. I. Anchekov, O. V. Nagoeva, O. B. Makarevich, Yu. Kh. Khamukov, D. G. Tokmakova, “Interactive multimodal training
of cognitive self-organizing systems
of natural language control over missions
of multiagent robots”, News of the Kabardin-Balkar scientific center of RAS, 2015, no. 1, 9–15 |
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2014 |
| 28. |
O. V. Nagoeva, D. Y. Zaporozhets, R. A. Shankov, A. M. Kagazezhev, “Systems of understanding of the speech and models
of semantics representations”, News of the Kabardin-Balkar scientific center of RAS, 2014, no. 5, 40–48 |
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2012 |
| 29. |
V. Ch. Kudaev, Z. V. Nagoev, O. V. Nagoeva, “Recursive agents for problems of modelling
intellectual decision-making
on the basis of self-organising multiagent
cognitive architectures”, News of the Kabardin-Balkar scientific center of RAS, 2012, no. 4, 50–57 |
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2011 |
| 30. |
O. V. Nagoeva, “Statement of the problem of formation
of optimum behaviour
of the generalized economic agent
in the intellectual inhabitancy”, News of the Kabardin-Balkar scientific center of RAS, 2011, no. 1, 205–212 |
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