We consider model-based reinforcement learning in finite Markov Decision Processes (MDPs), focussing on so-called optimistic strategies. Optimism is usually implemented by carryin...
A scenario in ontology development and its use is hypothesis testing, such as finding new subconcepts based on the data linked to the ontology. During such experimentation, knowle...
K nearest neighbor classifier (K-NN) is widely discussed and applied in pattern recognition and machine learning, however, as a similar lazy classifier using local information for...
: Privacy is one of the most important properties of an information system must satisfy, in which systems the need to share information among different, not trusted entities, the p...
—This paper introduces a new algorithm for probabilistic motion planning in arbitrary, uncertain vector fields, with emphasis on high-level planning for Montgolfier´e balloons...
Michael T. Wolf, Lars Blackmore, Yoshiaki Kuwata, ...