Abstract. Reinforcement learning (RL) is a widely used learning paradigm for adaptive agents. There exist several convergent and consistent RL algorithms which have been intensivel...
Lucian Busoniu, Damien Ernst, Bart De Schutter, Ro...
Abstract. We introduce a framework, based on logic programming, for preferential reasoning with agents on the Semantic Web. Initially, we encode the knowledge of an agent as a logi...
Stijn Heymans, Davy Van Nieuwenborgh, Dirk Vermeir
Abstract. An over-zealous machine learner can automatically generate large, intricate, theories which can be hard to understand. However, such intricate learning is not necessary i...
Abstract. Logic programming has often been considered less than adequate for modelling the dynamics of knowledge changing over time. In this paper we describe Evolving Logic Progra...
Abstract. Logic programming has often been considered less than adequate for modelling the dynamics of knowledge changing over time. Evolving Logic Programs (EVOLP) has been recent...