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Allen, C., Balavzevi'c, I., & Hospedales, T. (2020). A probabilistic framework for discriminative and neuro-symbolic semi-supervised learning. arXiv preprint arXiv:2006.05896.  
26/11/2020, 03:01
Arabshahi, F., Lee, J., Gawarecki, M., Mazaitis, K., Azaria, A., & Mitchell, T. (2020). Conversational neuro-symbolic commonsense reasoning. arXiv preprint arXiv:2006.10022.  
26/11/2020, 02:54
Baker, S., & Xiang, W. (2023). Artificial intelligence of things for smarter healthcare: A survey of advancements, challenges, and opportunities. IEEE Communications Surveys & Tutorials.  
11/07/2023, 14:30
Ballard, D. H., Hayhoe, M. M., Pook, P. K., & Rao, R. P. (1997). Deictic codes for the embodiment of cognition. Behavioral and brain sciences, 20(4), 723–742.  
09/11/2023, 19:19
Bhovad, P., & Li, S. (2021). Physical reservoir computing with origami and its application to robotic crawling. Scientific reports, 11(1), 1–18.  
01/11/2021, 11:18
Bianchini, F. (2023). Autopoiesis of the artificial: From systems to cognition. Biosystems, 104936.  
19/02/2024, 20:46
Blasch, E., Schuck, T., & Gagne, O. B. (2021). Trusted entropy-based information maneuverability for ai information systems engineering. In Engineering Artificially Intelligent Systems (pp. 34–52). Springer.  
21/07/2022, 10:16
Bonabeau, E., Dorigo, M., & Theraulaz, G. (1999). Swarm intelligence: From natural to artificial systems. Oxford University Press.  
09/11/2023, 19:03
Brester, C., Semenkin, E., & others. (2013). Development of adaptive genetic algorithms for neural network models multicriteria design. Вестник СибГАУ, (4), 99.  
06/08/2020, 09:41
C'ardenas-Garc'ia, J. F. (2023). Info-autopoiesis and the limits of artificial general intelligence. Computers, 12(5), 102.  
19/02/2024, 21:14
Caron, J. F. (2018). A theory of the super soldier: The morality of capacity-increasing technologies in the military. Manchester University Press.  
29/06/2020, 11:29
Chiu, S., Araiza Illan, D., & Eder, K. Bio-inspired self-preservation to protect robots from threats. in towards autonomous robotic systems 18th annual conference, taros 2017, guildford, uk, july 19--21, 2017, proceedings (pp. 166-181).(lecture notes in computer science (including lecture notes in artificial intelligence). TAROS.  
05/10/2021, 15:28
Conway, C. M., & Christiansen, M. H. (2005). Modality-constrained statistical learning of tactile, visual, and auditory sequences. Journal of Experimental Psychology: Learning, Memory, and Cognition, 31(1), 24–39.  
02/06/2021, 08:15
Correia, L., Sebasti ao, A. M., & Santana, P. (2017). On the role of stigmergy in cognition. Progress in Artificial Intelligence, 6, 79–86.  
09/11/2023, 15:02
De Luca Picione, R. (2021). The dynamic nature of the human psyche and its three tenets: Normativity, liminality and resistance—semiotic advances in direction of modal articulation sensemaking. Human Arenas, 4(2), 279–293.  
17/03/2024, 19:29
De Raedt, L., Dumanvci'c, S., Manhaeve, R., & Marra, G. (2020). From statistical relational to neuro-symbolic artificial intelligence. arXiv preprint arXiv:2003.08316.  
26/11/2020, 02:41
Duffy, B. R., O’hare, G. M., Martin, A. N., Bradley, J. F., & Schoen, B. 2003, Agent chameleons: Moving minds. Paper presented at Proceedings of The IEEE Systems, Man & Cybernetics Workshop (UK & ROI Chapter).  
04/10/2021, 13:53
Fodor, J. A. (1983). The modularity of mind. MIT Press.  
19/07/2023, 14:03
Fornito, A., Zalesky, A., & Bullmore, E. (2016). Fundamentals of brain network analysis. Elsevier Science.  
25/06/2020, 11:03
Franklin, N. T., Norman, K. A., Ranganath, C., Zacks, J. M., & Gershman, S. J. (2020). Structured event memory: A neuro-symbolic model of event cognition. Psychological Review, 127(3), 327.  
26/11/2020, 02:50
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WIKINDX 6.7.0 | Total resources: 1621 | Username: -- | Bibliography: WIKINDX Master Bibliography | Style: American Psychological Association (APA)