Allen, C., Balavzevi'c, I., & Hospedales, T. (2020). A probabilistic framework for discriminative and neuro-symbolic semi-supervised learning. arXiv preprint arXiv:2006.05896 .
11/26/20, 3:01 AM
Anantrasirichai, N., & Bull, D. (2022). Artificial intelligence in the creative industries: A review. Artificial Intelligence Review , 1–68.
3/17/23, 8:13 PM
Arabshahi, F., Lee, J., Gawarecki, M., Mazaitis, K., Azaria, A., & Mitchell, T. (2020). Conversational neuro-symbolic commonsense reasoning. arXiv preprint arXiv:2006.10022 .
11/26/20, 2:54 AM
Attfield, S., & Baber, C. 2017, Elaborating the frames of data-frame theory . Paper presented at 13th International conference on Naturalistic Decision Making.
6/18/23, 7:31 PM
Balakrishnan, A. (2021). Productizing an artificial intelligence solution for intelligent detail extraction—synergy of symbolic and sub-symbolic artificial intelligence techniques. Trends of Data Science and Applications: Theory and Practices , 954 , 23.
1/24/22, 12:39 PM
Barnden, J. A., & Lee, M. G. (2001). Metaphor and artificial intelligence . Lawrence Erlbaum Associates.
9/20/21, 12:59 PM
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 .
11/8/21, 1:19 PM
Bender, E. A. (1996). Mathematical methods in artificial intelligence. IEEE Computer Society Press .
1/25/22, 10:26 AM
Bhovad, P., & Li, S. (2021). Physical reservoir computing with origami and its application to robotic crawling. Scientific reports , 11 (1), 1–18.
11/1/21, 11:18 AM
Bianchini, F. (2023). Autopoiesis of the artificial: From systems to cognition. Biosystems , 104936.
2/19/24, 8:46 PM
Bommasani, R., Hudson, D. A., Adeli, E., Altman, R., Arora, S., & von Arx, S., et al.. (2021). On the opportunities and risks of foundation models. arXiv preprint arXiv:2108.07258 .
8/23/21, 11:56 AM
Botschen, T., Sorokin, D., & Gurevych, I. 2018, Frame-and entity-based knowledge for common-sense argumentative reasoning . Paper presented at Proceedings of the 5th Workshop on Argument Mining.
9/26/22, 7:12 PM
Brown, N., & Sandholm, T. (2019). Superhuman ai for multiplayer poker. Science , 365 (6456), 885–890.
3/16/21, 8:12 AM
Calegari, R., Omicini, A., & Sartor, G. 2020, Explainable and ethical ai: A perspective on argumentation and logic programming . Paper presented at International Conference of the Italian Association for Artificial Intelligence.
9/19/22, 2:23 PM
Chen, M., Herrera, F., & Hwang, K. (2018). Cognitive computing: Architecture, technologies and intelligent applications. IEEE Access , 6 , 19774–19783.
12/2/20, 12:21 PM
Choudhary, T., Mishra, V., Goswami, A., & Sarangapani, J. (2020). A comprehensive survey on model compression and acceleration. Artificial Intelligence Review , 1–43.
6/2/21, 8:18 AM
Crowder, J. A., Carbone, J., & Friess, S. (2020). Abductive artificial intelligence learning models. In Artificial Psychology (pp. 51–63). Springer.
8/30/21, 9:25 AM
Dai, W.-Z., Xu, Q., Yu, Y., & Zhou, Z.-H. (2019). Bridging machine learning and logical reasoning by abductive learning. 33rd Conference on Neural Information Processing Systems .
8/30/21, 9:15 AM
Davis, E., & Marcus, G. (2015). Commonsense reasoning and commonsense knowledge in artificial intelligence. Communications of the ACM , 58 (9), 92–103.
12/3/20, 9:25 AM
De Raedt, L., Dumanvci'c, S., Manhaeve, R., & Marra, G. (2020). From statistical relational to neuro-symbolic artificial intelligence. arXiv preprint arXiv:2003.08316 .
11/26/20, 2:41 AM
