Partial knowledge about geospatial categories is critical for knowledge modelling in the geospatial domain but is beyond the scope of conventional ontologies. Degree of overlaps be...
—Reinforcement learning (RL) is a valuable learning method when the systems require a selection of control actions whose consequences emerge over long periods for which input– ...
We describe a method for selecting optimal actions affecting the sensors in a probabilistic state estimation framework, with an application in selecting optimal zoom levels for a ...
Benjamin Deutsch, Matthias Zobel, Joachim Denzler,...
— Intention recognition is an important topic in human-robot cooperation that can be tackled using probabilistic model-based methods. A popular instance of such methods are Bayes...
Oliver C. Schrempf, David Albrecht, Uwe D. Hanebec...
We propose and evaluate a decision-theoretic approach for selecting tutorial actions by looking ahead to anticipate their effects on the student and other aspects of the tutorial s...