Obtaining large volumes of inference knowledge, such as entailment rules, has become a major factor in achieving robust semantic processing. While there has been substantial resea...
We propose a simple approach to combining first-order logic and probabilistic graphical models in a single representation. A Markov logic network (MLN) is a first-order knowledge b...
The application of AI planning techniques to manufacturing systems is being widely deployed for all the tasks involved in the process, from product design to production planning an...
Abstract. We introduce an ontology-based semantic modelling framework that addresses subject domain modelling, instruction modelling, and interoperability aspects in the developmen...
The objective of this work is to interpret inductive results obtained by the unsupervised learning method OSHAM. We briefly introduce the learning process of OSHAM, that extracts ...