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

Logistics (theme 3)
AAAI
M.M. Veloso
International Joint Conference on Artificial Intelligence
Networks and Optimization

Bader, S, Hitzler, P, Hölldobler, S, & Witzel, S. 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.