Inductive Logic Programming

A Refinement Operator for Theories.- Learning Logic Programs with Neural Networks.- A Genetic Algorithm for Propositionalization.- Classifying Uncovered Examples by Rule Stretching.- Relational Learning Using Constrained Confidence-Rated Boosting.- Induction, Abduction, and Consequence-Finding.- From Shell Logs to Shell Scripts.- An Automated ILP Server in the Field of Bioinformatics.- Adaptive Bayesian Logic Programs.- Towards Combining Inductive Logic Programming with Bayesian Networks.- Demand-Driven Construction of Structural Features in ILP.- Transformation-Based Learning Using Multirelational Aggregation.- Discovering Associations between Spatial Objects: An ILP Application.- ?-Subsumption in a Constraint Satisfaction Perspective.- Learning to Parse from a Treebank: Combining TBL and ILP.- Induction of Stable Models.- Application of Pruning Techniques for Propositional Learning to Progol.- Application of ILP to Cardiac Arrhythmia Characterization for Chronicle Recognition.- Efficient Cross-Validation in ILP.- Modelling Semi-structured Documents with Hedges for Deduction and Induction.- Learning Functions from Imperfect Positive Data.

Includes supplementary material: sn.pub/extras