Probabilistic logic programming is a powerful technique to represent and reason with imprecise probabilistic knowledge. A probabilistic logic program (PLP) is a knowledge base whi...
In spite of the increasing effort spent on building ontologies for the Semantic Web, little attention has been paid to the impact of these ontologies on knowledge-based intelligen...
A novel and simple combination of inductive logic programming with kernel methods is presented. The kFOIL algorithm integrates the well-known inductive logic programming system FO...
Niels Landwehr, Andrea Passerini, Luc De Raedt, Pa...
We present probabilistic logic programming under inheritance with overriding. This approach is based on new notions of entailment for reasoning with conditional constraints, which...
In inductive logic programming, subsumption is a widely used coverage test. Unfortunately, testing -subsumption is NP-complete, which represents a crucial efficiency bottleneck fo...