— Incremental rule base learning techniques can be used to learn models and classifiers from interval or fuzzyvalued data. These algorithms are efficient when the observation e...
If robots learn new actions through human-robot interaction, it is important that the robots can utilize rewards as well as instructions to reduce humans' efforts. Additionall...
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...
— In this paper we address the reliability of policies derived by Reinforcement Learning on a limited amount of observations. This can be done in a principled manner by taking in...
A new model for learning from multinomial data has recently been developed, giving predictive inferences in the form of lower and upper probabilities for a future observation. Apa...