Items where Author is "Lamb, L. C."
Article
Garcez, A. D. & Lamb, L. C. (2023). Neurosymbolic AI: the 3rd wave. Artificial Intelligence Review, 56(11), pp. 12387-12406. doi: 10.1007/s10462-023-10448-w
Garcez, A., Gori, M., Lamb, L. C. , Serafini, L., Spranger, M. & Tran, S. N. (2019). Neural-symbolic computing: An effective methodology for principled integration of machine learning and reasoning. Journal of Applied Logics, 6(4), pp. 611-631.
d'Avila Garcez, A. S., Gabbay, D. M. & Lamb, L. C. (2014). A neural cognitive model of argumentation with application to legal inference and decision making. Journal of Applied Logic, 12(2), pp. 109-127. doi: 10.1016/j.jal.2013.08.004
Borges, Rafael, Garcez, A. & Lamb, L. C. (2011). Learning and Representing Temporal Knowledge in Recurrent Networks. IEEE Transactions on Neural Networks, 22(12), pp. 2409-2421. doi: 10.1109/tnn.2011.2170180
Garcez, A., Lamb, L. C. & Gabbay, D. M. (2007). Connectionist modal logic: Representing modalities in neural networks. Theoretical Computer Science, 371(1-2), pp. 34-53. doi: 10.1016/j.tcs.2006.10.023
Garcez, A., Gabbay, D. M. & Lamb, L. C. (2005). Value-based argumentation frameworks as neural-symbolic learning systems. Journal of Logic and Computation, 15(6), pp. 1041-1058. doi: 10.1093/logcom/exi057
Book Section
de Penning, L., Garcez, A., Lamb, L. C. & Meyer, J-J. C. (2011). A Neural-Symbolic Cognitive Agent for Online Learning and Reasoning. In: Proceedings of the Twenty-Second international joint conference on Artificial Intelligence. (pp. 1653-1658). International Joint Conferences on Artificial Intelligence. doi: 10.5591/978-1-57735-516-8/IJCAI11-278
Conference or Workshop Item
Carvalho, B. W., d’Avila Garcez, A. S. 
ORCID: 0000-0001-7375-9518 & Lamb, L. C. (2023).
Graph-based Neural Modules to Inspect Attention-based Architectures: A Position Paper.
In:
CEUR Workshop Proceedings.
Thinking Fast and Slow and Other Cognitive Theories in AI a AAAI 2022 Fall Symposium, 17-19 Nov 2022, Arlington, Virginia, US.
Garcez, A., Besold, T. R., Raedt, L. , Foldiak, P., Hitzler, P., Icard, T., Kuhnberger, K-U., Lamb, L. C., Miikkulainen, R. & Silver, D. L. (2015). Neural-Symbolic Learning and Reasoning: Contributions and Challenges. Paper presented at the 2015 AAAI Spring Symposium Series, 23-03-2015 - 25-03-2015, Stanford University, USA.
Report
Garcez, A., Gabbay, D. M. & Lamb, L. C. (2004). Argumentation Neural Networks: Value-based Argumentation Frameworks as Neural-Symbolic Learning Systems (TR/2004/DOC/01). .