Most work on preference learning has focused on pairwise preferences or rankings over individual items. In this paper, we present a method for learning preferences over sets of it...
Decision-theoretic reasoning and planning algorithms are increasingly being used for mobile robot navigation, due to the signi cant uncertainty accompanying the robots' perce...
As opposed to traditional supervised learning, multiple-instance learning concerns the problem of classifying a bag of instances, given bags that are labeled by a teacher as being...
The question investigated in this paper is to what extent an input representation influences the success of learning, in particular from the point of view of analyzing agents that...
Nowadays most universities use different distance learning environments. However in the educational process besides forums, chats and other collaborative possibilities the content...