Inductive Logic Programming: From Machine Learning to Software Engineering
Inductive Logic Programming: From Machine Learning to Software Engineering
Inductive Logic Programming: Techniques and Applications
Inductive Logic Programming: Techniques and Applications
On the Proper Definition of Minimality in Specialization and Theory Revision
ECML '93 Proceedings of the European Conference on Machine Learning
Learning Non-Monotonic Logic Programs: Learning Exceptions
ECML '95 Proceedings of the 8th European Conference on Machine Learning
Strategies in Combined Learning via Logic Programs
Machine Learning - Special issue on multistrategy learning
Representation of Incomplete Knowledge by Induction of Default Theories
LPNMR '01 Proceedings of the 6th International Conference on Logic Programming and Nonmonotonic Reasoning
Nonmonotonic Inductive Logic Programming
LPNMR '01 Proceedings of the 6th International Conference on Logic Programming and Nonmonotonic Reasoning
ECSQARU '95 Proceedings of the European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty
A Simple Characterization of Extended Abduction
CL '00 Proceedings of the First International Conference on Computational Logic
Towards the Integration of Inductive and Nonmonotonic Logic Programming
Progress in Discovery Science, Final Report of the Japanese Discovery Science Project
Inverse Entailment in Nonmonotonic Logic Programs
ILP '00 Proceedings of the 10th International Conference on Inductive Logic Programming
Experimental study of discovering essential information from customer inquiry
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Induction of defeasible logic theories in the legal domain
ICAIL '03 Proceedings of the 9th international conference on Artificial intelligence and law
Induction from answer sets in nonmonotonic logic programs
ACM Transactions on Computational Logic (TOCL)
Ordering default theories and nonmonotonic logic programs
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
Outlier detection using default reasoning
Artificial Intelligence
Dealing Automatically with Exceptions by Introducing Specificity in ASP
ECSQARU '09 Proceedings of the 10th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Determination of general concept in learning default rules
PRICAI'00 Proceedings of the 6th Pacific Rim international conference on Artificial intelligence
Exploring relations between answer set programs
Logic programming, knowledge representation, and nonmonotonic reasoning
Adaptive reasoning for cooperative agents
INAP'09 Proceedings of the 18th international conference on Applications of declarative programming and knowledge management
| Hi-index | 0.00 |
This paper presents a method to generate nonmonotonic rules with exceptions from positive/ negative examples and background knowledge in Inductive Logic Programming. We adopt extended logic programs as the form of programs to be learned, where two kinds of negation--negation as failure and classical negation--are effectively used in the presence of incomplete information. While default rules axe generated as specialization of general rules that cover positive examples, exceptions to general rules are identified from negative examples and are then generalized to rules for cancellation of defaults. We implemented the learning system LELP based on the proposed method. In LELP, when the numbers of positive and negative examples are very close, either parallel default rules with positive and negative consequents or nondeterministic rules are learned. Moreover, hierarchical defaults can also be learned by recursively calling the exception identification algorithm.