Combining Symbolic and Neural Learning
Machine Learning
Knowledge-based artificial neural networks
Artificial Intelligence
Inductive logic programming: issues, results and the challenge of learning language in logic
Artificial Intelligence - Special issue on applications of artificial intelligence
Advances in Inductive Logic Programming
Advances in Inductive Logic Programming
Inductive Logic Programming: Techniques and Applications
Inductive Logic Programming: Techniques and Applications
The Connectionist Inductive Learning and Logic Programming System
Applied Intelligence
Learning Logical Definitions from Relations
Machine Learning
Learning Conjunctive Concepts in Structural Domains
Machine Learning
FONN: Combining First Order Logic with Connectionist Learning
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Towards a Hybrid Model of First-Order Theory Refinement
Hybrid Neural Systems, revised papers from a workshop
A Framework for Defining Distances Between First-Order Logic Objects
ILP '98 Proceedings of the 8th International Workshop on Inductive Logic Programming
Approximate ILP Rules by Backpropagation Neural Network: A Result on Thai Character Recognition
ILP '99 Proceedings of the 9th International Workshop on Inductive Logic Programming
Refining Complete Hypotheses in ILP
ILP '99 Proceedings of the 9th International Workshop on Inductive Logic Programming
Tractable induction and classification in first order logic via stochastic matching
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Rule induction and instance-based learning a unified approach
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Cascade ARTMAP: integrating neural computation and symbolic knowledge processing
IEEE Transactions on Neural Networks
Towards a Theory Revision Approach for the Vertical Fragmentation of Object Oriented Databases
SBIA '02 Proceedings of the 16th Brazilian Symposium on Artificial Intelligence: Advances in Artificial Intelligence
A Statistical Approach to Incremental Induction of First-Order Hierarchical Knowledge Bases
ILP '08 Proceedings of the 18th international conference on Inductive Logic Programming
ProGolem: a system based on relative minimal generalisation
ILP'09 Proceedings of the 19th international conference on Inductive logic programming
Classifying relational data with neural networks
ILP'05 Proceedings of the 15th international conference on Inductive Logic Programming
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First-order theory refinement using neural networks is still an open problem. Towards a solution to this problem, we use inductive logic programming techniques to introduce FOCA, a First-Order extension of the Cascade ARTMAP system. To present such a first-order extension of Cascade ARTMAP, we: a) modify the network structure to handle first-order objects; b) define first-order versions of the main functions that guide all Cascade ARTMAP dynamics, the choice and match functions; c) define a first-order version of the propositional learning algorithm to approximate Plotkin's least general generalization. Preliminary results indicate that our initial goal of learning logic programs using neural networks can be achieved.