Model-based Bayesian reinforcement learning has generated significant interest in the AI community as it provides an elegant solution to the optimal exploration-exploitation trade...
By learning a range of possible times over which the effect of an action can take place, a robot can reason more effectively about causal and contingent relationships in the world...
Abstract. This paper presents a methodology for automatically customizing a scenario to suit a learner’s abilities, needs, or goals. Training scenarios are often utilized to give...
Temporal reasoners for document understanding typically assume that a document’s creation date is known. Algorithms to ground relative time expressions and order events often re...
As information and communication technologies are becoming an integral part of our homes, the demand for AmI systems with assistive functionality is increasing. A great effort has...
Todor Dimitrov, Josef Pauli, Edwin Naroska, Christ...