On the declarative semantics of deductive databases and logic programs
Foundations of deductive databases and logic programming
Logic programs with classical negation
Logic programming
Induction as nonmonotonic inference
Proceedings of the first international conference on Principles of knowledge representation and reasoning
Automated Refinement of First-Order Horn-Clause Domain Theories
Machine Learning
Strategies in Combined Learning via Logic Programs
Machine Learning - Special issue on multistrategy learning
Logical characterisations of inductive learning
Handbook of defeasible reasoning and uncertainty management systems
Foundations of Inductive Logic Programming
Foundations of Inductive Logic Programming
Answer set programming and plan generation
Artificial Intelligence
Logic programs with stable model semantics as a constraint programming paradigm
Annals of Mathematics and Artificial Intelligence
Learning Logical Definitions from Relations
Machine Learning
Knowledge Representation with Logic Programs
LPKR '97 Selected papers from the Third International Workshop on Logic Programming and Knowledge Representation
The Many Faces of Inductive Logic Programming
ISMIS '93 Proceedings of the 7th International Symposium on Methodologies for Intelligent Systems
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
Learning Non-Monotonic Logic Programs: Learning Exceptions
ECML '95 Proceedings of the 8th European Conference on Machine Learning
The Diagnosis Frontend of the dlv system
AI Communications
Learning extended logic programs
IJCAI'97 Proceedings of the 15th international joint conference on Artifical intelligence - Volume 1
Ordering default theories and nonmonotonic logic programs
Theoretical Computer Science
Any-world assumptions in logic programming
Theoretical Computer Science
Nonmonotonic inductive logic programming by instance patterns
Proceedings of the 9th ACM SIGPLAN international conference on Principles and practice of declarative programming
Extracting Requirements from Scenarios with ILP
Inductive Logic Programming
ILP '08 Proceedings of the 18th international conference on Inductive Logic Programming
How Flexible Is Answer Set Programming? An Experiment in Formalizing Commonsense in ASP
LPNMR '09 Proceedings of the 10th International Conference on Logic Programming and Nonmonotonic Reasoning
Exploring relations between answer set programs
Logic programming, knowledge representation, and nonmonotonic reasoning
Inductive equivalence of logic programs
ILP'05 Proceedings of the 15th international conference on Inductive Logic Programming
Learning from interpretation transition
Machine Learning
Hi-index | 0.00 |
Inductive logic programming (ILP) realizes inductive machine learning in computational logic. However, the present ILP mostly handles classical clausal programs, especially Horn logic programs, and has limited applications to learning nonmonotonic logic programs. This article studies a method for realizing induction in nonmonotonic logic programs. We consider an extended logic program as a background theory, and introduce techniques for inducing new rules using answer sets of the program. The produced new rules explain positive/negative examples in the context of inductive logic programming. The proposed methods extend the present ILP techniques to a syntactically and semantically richer framework, and contribute to a theory of nonmonotonic ILP.