Voir la notice de l'article provenant de la source Math-Net.Ru
@article{IZKAB_2023_5_a2, author = {I. A. Pshenokova and A. Z. Apshev}, title = {Energy exchange model between agneurons as part}, journal = {News of the Kabardin-Balkar scientific center of RAS}, pages = {32--40}, publisher = {mathdoc}, number = {5}, year = {2023}, language = {ru}, url = {http://geodesic.mathdoc.fr/item/IZKAB_2023_5_a2/} }
I. A. Pshenokova; A. Z. Apshev. Energy exchange model between agneurons as part. News of the Kabardin-Balkar scientific center of RAS, no. 5 (2023), pp. 32-40. http://geodesic.mathdoc.fr/item/IZKAB_2023_5_a2/
[1] A. Dorri, S. Kanhere, R. Jurdak, “Multi-agent systems: A Survey”, IEEE Access, 6 (2018), 28573–28593 | DOI
[2] A. Bond, L. Gasser, Readings in distributed artificial intelligence, Morgan Kaufmann, San Mateo, CA, USA, 2014, 668 pp.
[3] M. Wooldridge, An Introduction to multiagent systems, Wiley, New York, 2009, 488 pp.
[4] S. Shamshirband, N. Anuar, M. Kiah, A. Patel, “An appraisal and design of a multi-agent system based cooperative wireless intrusion detection computational intelligence technique”, Eng. Appl. Artif. Intell, 26 (2013), 2105–2127 | DOI
[5] A. M. Zou, K. Kumar, Z. G. Hou, “Distributed consensus control for multi-agent systems using terminal sliding mode and Chebyshev neural networks”, Int. J. Robust Nonlinear Control, 23(3) (2013), 334–357 | DOI | MR | Zbl
[6] D. Calvaresi et al., “Real-time multi-agent systems: rationality, formal model, and empirical results”, Autonomous agents and multi-agent systems, 35:1 (2021), 12 | DOI
[7] D. Zhang et al., “Physical safety and cyber security analysis of multi-agent systems: A survey of recent advances”, IEEE/CAA Journal of automatica sinica, 8:2 (2021), 319–333 | DOI | MR
[8] H. Rezaee, F. Abdollahi, “Average consensus over high-order multiagent systems”, IEEE Trans. autom. control, 60:11 (2015), 3047–3052 | DOI | MR | Zbl
[9] L. Ma, H. Min, S. Wang et al., “An overview of research in distributed attitude coordination control”, IEEE/CAA J. autom. sinica, 2:2 (2015), 121–133 | DOI | MR
[10] Z. Nagoev, I. Pshenokova, O. Nagoeva et al., “Learning algorithm for an intelligent decision making system based on multi-agent neurocognitive architectures”, Cognitive systems research, 66 (2021), 82–88 | DOI
[11] Z. V. Nagoev, Intellectics, or thinking in natural and artificial systems, Izdatel'stvo KBNTS RAN, Nal'chik:, 2013, 211 pp.
[12] Z. V. Nagoev, “Multi-agent existential mappings and functions”, News of the Kabardino-Balkarian Scientific Center of RAS, 2013, no. 4 (54), 63–71
[13] Z. Nagoev, I. Pshenokova, O. Nagoeva et al., “Situational analysis model in an intelligent system based on multi-agent neurocognitive architectures”, Journal of Physics: Conference Series, 2021, 022103 | DOI | Zbl
[14] M. Picard, B. S. McEwen, “Mitochondria impact brain function and cognition”, Proceedings of the National Academy of Sciences, 111:1 (2014), 7–8 | DOI
[15] D. C. Wallace, “Bioenergetics, the origins of complexity, and the ascent of man”, Proceedings of the National Academy of Sciences, 107, supplement 2 (2010), 8947–8953 | DOI
[16] D. C. Chan, “Fusion and fission: interlinked processes critical for mitochondrial health”, Annual Review of genetics, 46 (2012), 265–287 | DOI
[17] I. A. Pshenokova, O. V. Nagoeva, A. Z. Apshev et al, “Formation of dynamic cause-and-effect relationships in controlling the behavior of an intelligent agent based on the formalism of multiagent neurocognitive architectures”, News of the Kabardino-Balkarian Scientific Center of RAS, 2022, no. 5 (109), 73–80 | DOI | DOI
[18] M. E. Raichle, D. A. Gusnard, “Appraising the brain's energy budget”, PNAS, 99:16 (2002), 10237–10239 | DOI
[19] M. Bruckmaier, I. Tachtsidis, P. e al. Phan, “Attention and Capacity Limits in Perception: A Cellular Metabolism Account”, Journal of Neuroscience, 2020, 6801–6811 | DOI