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Abbass, H. A. (2019). Social integration of artificial intelligence: Functions, automation allocation logic and human-autonomy trust. Cognitive Computation, 11(2), 159–171.  
21/06/2021, 11:26
Abbeel, P., Coates, A., Quigley, M., & Ng, A. (2006). An application of reinforcement learning to aerobatic helicopter flight. Advances in Neural Information Processing Systems, 19.  
19/02/2024, 15:11
Abdel-Basset, M., Gamal, A., Moustafa, N., Abdel-Monem, A., & El-Saber, N. (2021). A security-by-design decision-making model for risk management in autonomous vehicles. IEEE Access, 9, 107657–107679.  
14/06/2023, 18:25
Aberdeen, D., Thi'ebaux, S., Zhang, L., & others. 2004, Decision-theoretic military operations planning.. Paper presented at ICAPS.  
30/06/2020, 09:40
AKG"UL, A. (2015). Artificial intelligence military applications. Ankara {"U}niversitesi SBF Dergisi, 45(1).  
30/06/2020, 09:12
Albarado, K., Coduti, L., Aloisio, D., Robinson, S., Drown, D., & Javorsek, D. (2021). Alphamosaic: An artificially intelligent battle management architecture. Journal of Aerospace Information Systems, 1–11.  
18/01/2022, 19:59
Ali-Tolppa, J., Kocsis, S., Schultz, B., Bodrog, L., & Kajo, M. 2018, Self-healing and resilience in future 5g cognitive autonomous networks. Paper presented at 2018 ITU Kaleidoscope: Machine Learning for a 5G Future (ITU K).  
07/09/2021, 09:03
Alkire, B., Hanser, L. M., & Lingel, S. L. (2018). A wargame method for assessing risk and resilience of military command-and-control organizations. Rand.  
22/11/2021, 14:35
Allen, G. C. (2019). Understanding china's ai strategy: Clues to chinese strategic thinking on artificial intelligence and national security. Center for a New American Security Washington, DC.  
29/06/2020, 13:44
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
Alt, C., H"ubner, M., & Hennig, L. (2019). Fine-tuning pre-trained transformer language models to distantly supervised relation extraction. arXiv preprint arXiv:1906.08646.  
06/10/2020, 13:17
Amoroso, D., Frank, S., Noel, S., Lucy, S., & Guglielmo, T. (2018). Autonomy in weapon systems: The military application of artificial intelligence as a litmus test for germany’s new foreign and security policy. Autonomy in Weapon Systems.  
02/07/2020, 11:33
Anderljung, M., Barnhart, J., Leung, J., Korinek, A., O'Keefe, C., & Whittlestone, J., et al.. (2023). Frontier ai regulation: Managing emerging risks to public safety. arXiv preprint arXiv:2307.03718.  
23/10/2023, 17:28
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
Arora, S., & Doshi, P. (2021). A survey of inverse reinforcement learning: Challenges, methods and progress. Artificial Intelligence, 297, 103500.  
19/02/2024, 21:45
Ayoub, K., & Payne, K. (2016). Strategy in the age of artificial intelligence. Journal of strategic studies, 39(5-6), 793–819.  
29/06/2020, 14:18
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
Beaulieu, S., Frati, L., Miconi, T., Lehman, J., Stanley, K. O., & Clune, J., et al.. (2020). Learning to continually learn. arXiv preprint arXiv:2002.09571.  
08/11/2021, 13:19
Bengio, Y., Lecun, Y., & Hinton, G. (2021). Deep learning for ai. Communications of the ACM, 64(7), 58–65.  
18/01/2023, 12:34
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
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WIKINDX 6.7.0 | Total resources: 1621 | Username: -- | Bibliography: WIKINDX Master Bibliography | Style: American Psychological Association (APA)