Factored representations, model-based learning, and hierarchies are well-studied techniques for improving the learning efficiency of reinforcement-learning algorithms in large-sca...
Carlos Diuk, Alexander L. Strehl, Michael L. Littm...
Abstract. Cost-based filtering is a novel approach that combines techniques from Operations Research and Constraint Programming to filter from decision variable domains values that...
Abstract. We introduce domain-restricted RDF (dRDF) which allows to associate an RDF graph with a fixed, finite domain that interpretations for it may range over. We show that dRDF...
Reinhard Pichler, Axel Polleres, Fang Wei, Stefan ...
Abstract. Question answering systems aim to meet users' information needs by returning exact answers in response to a question. Traditional open domain question answering syst...
Abstract. In this paper we present a theory-based approach to designing tailorable groupware for the healthcare domain. Both literature and empirical data show the need, and diffic...