Вдъхновени от мозъка модели и техни приложения
DOI :
https://doi.org/10.55630/mem.2025.54.018-024Ключови думи :
изкуствен интелект, невробиология, невроморфни изчисленияАбстракт
Въпреки, че съвременния изкуствен интелект (ИИ) стана мощно средство в мно- го области и дори в ежедневието ни, той все още не може да работи по-добре от човешкия мозък. Естествения интелект е резултат от съвместната работа нa групи от нервни клетки имащи много по-сложна функционалност и връзки отколкото из- куствените невронни мрежи. Статията представя основните принципи на работа на мозъка, вдъхновените от тях невроморфни изчисления и техни приложения.
Литература (библиография)
M. Barnell, C. Raymond, M. Wilson, D. Isereau, E. Cote, D. Brow., C. Cicotta. Demonstrating Advanced Machine Learning and Neuromorphic Computing Using IBM’s NS16e (2020) Advances in Intelligent Systems and Computing, 1228 AISC, pp. 1-11 DOI: 10.1007/978-3-030-52249-0_1
Z. Cai, X. Li. Neuromorphic Brain-Inspired Computing with Hybrid Neural Networks (2021) 2021 IEEE International Conference on Artificial Intelligence and Industrial Design, AIID 2021, art. no. 9456483, pp. 343-347 DOI: 10.1109/AIID51893.2021.9456483
L. Cheng, Y. Liu. Spiking neural networks: Model, learning algorithms and applications (2018) Kongzhi yu Juece/Control and Decision, 33 (5), pp. 923-937 DOI: 10.13195/j.kzyjc.2017.1444
A. Goriely. Eighty-six billion and counting: do we know the number of neurons in the human brain?, Brain, (2024) awae390, DOI: 10.1093/brain/awae390
Guetig et al. Learning input correlations through nonlinear temporally asymmetric hebbian plasticity (2003) Journal of Neuroscience 23, pp. 3697-3714 DOI: 10.1523/JNEUROSCI.23-09-03697.2003
E. M. Izhikevich. Simple Model of Spiking Neurons IEEE Transactions on Neural Networks (2003) 14, pp. 1569-1572
J. Liu, H. Wu. Research hotspots and trends of brain-inspired intelligence (2021) Chinese Journal of Biomedical Engineering, 40 (1), pp. 91-98
Y. Lv, H. Chen, Q. Wang, X. Li, C. Xie, Z. Song. Post-silicon nano-electronic device and its application in brain-inspired chips (2022) Frontiers in Neurorobotics, 16, art. no. 948386 DOI: 10.3389/fnbot.2022.948386
K. Roy, A. Jaiswal, P. Panda. Towards spike-based machine intelligence with neuromorphic computing (2019) Nature, 575 (7784), pp. 607-617 DOI: 10.1038/s41586-019-1677-2
R. S. Sutton, A. G. Barto. Reinforcement Learning: An Introduction, Second Edition, MIT Press, Cambridge, MA (2018)
R.-D. Wang, R. Wang, T.-D. Zhang, S. Wang. A Survey of Research on Robotic Brain-inspired Intelligence (2024) Zidonghua Xuebao/Acta Automatica Sinica, 50 (8), pp. 1485-1501 DOI: 10.16383/j.aas.c230705
Y. Wang, J. Lu, M. Gavrilova, R. A. Fiorini, J. Kacprzyk. Brain-Inspired Systems (BIS): Cognitive Foundations and Applications (2018) Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018, art. no. 8616173, pp. 995-1000 DOI: 10.1109/SMC.2018.00177