Inductive logic programming (ILP) and machine learning together represent a powerful synthesis of symbolic reasoning and statistical inference. ILP focuses on deriving interpretable logic rules ...

Inductive logic programming (ILP) studies the learning of (Prolog) logic programs and other relational knowledge from examples. Most machine learning algorithms are restricted to finite, propositional ...

<para>Recently, there has been increasing interest in Inductive Logic Programming (ILP) systems. But existing ILP systems cannot improve themselves automatically. This paper describes an Adaptive ...

This paper presents results from recent experiments with CHILL, a corpus-based parser acquisition system. CHILL treats grammar acquisition as the learning of search-control rules within a logic ...

Support logic programming and its practical implementation (Fril) integrates probabilistic and fuzzy uncertainty into logic programming using mass assignments. This paper presents a snapshot of ...