Compositional Q-Learning (CQ-L) (Singh 1992) is a modular approach to learning to performcomposite tasks made up of several elemental tasks by reinforcement learning. Skills acqui...
It is possible to model avatars that learn to simulate object manipulations and other complex actions. A number of applications may benefit from this technique including safety, e...
Abstract— We report on our experiences regarding the acquisition of hybrid Semantic 3D Object Maps for indoor household environments, in particular kitchens, out of sensed 3D poi...
Radu Bogdan Rusu, Zoltan Csaba Marton, Nico Blodow...
Recognition of player actions in broadcast sports video is a challenging task due to low resolution of the players in video frames. In this paper, we present a novel method to rec...
In this paper we present an agent language that combines agent functionality with an action theory and model-theoretic semantics. The language is based on abductive logic programmi...