Abstract— Imitation learning in robots, also called programing by demonstration, has made important advances in recent years, allowing humans to teach context dependant motor ski...
The problem of automatically selecting simulation models for autonomous agents depending on their current intentions and beliefs is considered in this paper. The intended use of t...
We introduce a model class for statistical learning which is based on mixtures of propositional rules. In our mixture model, the weight of a rule is not uniform over the entire ins...
This paper presents a method for improving any object tracking algorithm based on machine learning. During the training phase, important trajectory features are extracted which are...
Computational models of grounded language learning have been based on the premise that words and concepts are learned simultaneously. Given the mounting cognitive evidence for conc...