Ontology matching is currently a key technology to achieve the semantic alignment of ontological entities used by knowledge-based applications, and therefore to enable their inter...
When modelling complex systems one can not include all the causal factors, but one has to settle for partial models. This is alright if the factors left out are either so constant...
We present an algorithm, HI-MAT (Hierarchy Induction via Models And Trajectories), that discovers MAXQ task hierarchies by applying dynamic Bayesian network models to a successful...
The work presented in this paper explores a supervised method for learning a probabilistic model of a lexicon of VerbNet classes. We intend for the probabilistic model to provide ...
This paper describes the implementation and evaluation of a framework for modeling emotions in complex, decision-making agents. Sponsored by U.S. Army Research Institute (ARI), th...