In this paper we propose a random set framework for learning linguistic models for prediction problems. We show how we can model prediction problems based on learning linguistic p...
Abstract. In this paper we present an action/state-based logical framework for the analysis and verification of complex systems, which relies on the definition of doubly labelled...
Maurice H. ter Beek, Alessandro Fantechi, Stefania...
In various application domains there is a desire to compare process models, e.g., to relate an organization-specific process model to a reference model, to find a web service matc...
Ana Karla Alves de Medeiros, Wil M. P. van der Aal...
A technique for the credible modelling of economic agents with bounded rationality based on the evolutionary techniques is described. The genetic programming paradigm is most suite...
Visual modeling languages for discrete behavior modeling allow the modeler to describe how systems develop over time during system runs. Models of these languages are the basis fo...
Enrico Biermann, Claudia Ermel, Jonas Hurrelmann, ...