It is common to view programs as a combination of logic and control: the logic part de nes what the program must do, the control part how to do it. The Logic Programming paradigm ...
Markov Logic Networks (MLNs) have emerged as a powerful framework that combines statistical and logical reasoning; they have been applied to many data intensive problems including...
The utility problem occurs when the cost of the acquired knowledge outweighs its bene ts. When the learner acquires control knowledge for speeding up a problem solver, the bene t ...
Abstract. One of the most frequently used inference services of description logic reasoners classifies all named classes of OWL ontologies into a subsumption hierarchy. Due to emer...
Bayesian networks provide a modeling language and associated inference algorithm for stochastic domains. They have been successfully applied in a variety of medium-scale applicati...