2007
A Fully Connectionist Model Generator for Covered First-Order Logic Programs
Publication
Publication
Presented at the
International Joint Conference on Artificial Intelligence
We present a fully connectionist system for the learning of first-order logic programs and the generation of corresponding models: Given a program and a set of training examples, we embed the associated semantic operator into a feed-forward network and train the network using the examples. This results in the learning of first-order knowledge while damaged or noisy data is handled gracefully
| Additional Metadata | |
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| AAAI | |
| M.M. Veloso | |
| International Joint Conference on Artificial Intelligence | |
| Organisation | Networks and Optimization |
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Bader, S., Hitzler, P., Hölldobler, S., & Witzel, A. (2007). A Fully Connectionist Model Generator for Covered First-Order Logic Programs. In M. M. Veloso (Ed.), Proceedings of the 20th International Joint Conference on Artificial Intelligence (pp. 666–671). AAAI. |
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