Strategies in Combined Learning via Logic Programs
Machine Learning - Special issue on multistrategy learning
Foundations of Inductive Logic Programming
Foundations of Inductive Logic Programming
Knowledge Representation with Logic Programs
LPKR '97 Selected papers from the Third International Workshop on Logic Programming and Knowledge Representation
ILP '98 Proceedings of the 8th International Workshop on Inductive Logic Programming
Normal Programs and Multiple Predicate Learning
ILP '98 Proceedings of the 8th International Workshop on Inductive Logic Programming
Some Properties of Invers Resolution in Normal Logic Programs
ILP '99 Proceedings of the 9th International Workshop on Inductive Logic Programming
Inverse Entailment in Nonmonotonic Logic Programs
ILP '00 Proceedings of the 10th International Conference on Inductive Logic Programming
Learning Non-Monotonic Logic Programs: Learning Exceptions
ECML '95 Proceedings of the 8th European Conference on Machine Learning
Learning extended logic programs
IJCAI'97 Proceedings of the 15th international joint conference on Artifical intelligence - Volume 1
Nonmonotonic logics: meaning and utility
IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 1
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Commonsense reasoning and machine learning are two important topics in AI. These techniques are realized in logic programming as nonmonotonic logic programming (NMLP) and inductive logic programming (ILP), respectively. NMLP and ILP have seemingly different motivations and goals, but they have much in common in the background of problems. This article overviews the author's recent research results for realizing induction from nonmonotonic logic programs.