Many domain specialists are not familiar or comfortable with formal notations and formal tools like theorem provers or model generators. To address this problem we developed Attem...
First-order probabilistic logic is a powerful knowledge representation language. Unfortunately, deductive reasoning based on the standard semantics for this logic does not support...
A policy describes the conditions under which an action is permitted or forbidden. We show that a fragment of (multi-sorted) first-order logic can be used to represent and reason...
This paper presents an overview of recent systems for Inductive Logic Programming (ILP). After a short description of the two popular ILP systems FOIL and Progol, we focus on meth...
We present a fully connectionist system for the learning of first-order logic programs and the generation of corresponding models: Given a program and a set of training examples,...