Over the last few years, a few approaches have been proposed aiming to combine genetic and evolutionary computation (GECCO) with inductive logic programming (ILP). The underlying r...
Abstract--In the Relational Reinforcement learning framework, we propose an algorithm that learns an action model allowing to predict the resulting state of each action in any give...
In this work we present a backjumping technique for Disjunctive Logic Programming (DLP) under the Answer Set Semantics. It builds upon related techniques that had originally been p...
Collaboration has long been considered an effective approach to learning. However, forming optimal groups can be a time consuming and complex task. Different approaches have been ...
The definition of new concepts or roles for which extensional knowledge become available can turn out to be necessary to make a DL ontology evolve. In this paper we reformulate thi...