We describe an architecture for representing and managing context shifts that supports dynamic data interpretation. This architecture utilizes two layers of learning and three lay...
Nikita A. Sakhanenko, George F. Luger, Carl R. Ste...
Polysemy is one of the most difficult problems when dealing with natural language resources. Consequently, automated ontology learning from textual sources (such as web resources) ...
In this paper an omnidirectional Distributed Vision System (DVS) is presented. The presented DVS is able to learn to navigate a mobile robot in its working environment without any...
Emanuele Menegatti, C. Simionato, Stefano Tonello,...
We describe how to model the appearance of a 3-D object using multiple views, learn such a model from training images, and use the model for object recognition. The model uses pro...
Abstract— This paper proposes a simulation-based active policy learning algorithm for finite-horizon, partially-observed sequential decision processes. The algorithm is tested i...
Ruben Martinez-Cantin, Nando de Freitas, Arnaud Do...