This paper describes a new approach on how to teach a robot everyday manipulation tasks under the “Learning from Observation” framework. Most of the approaches so far assume t...
Koichi Ogawara, Jun Takamatsu, Hiroshi Kimura, Kat...
In this paper3 , we use Bayesian Networks as a means for unsupervised learning and anomaly (event) detection in gas monitoring sensor networks for underground coal mines. We show t...
X. Rosalind Wang, Joseph T. Lizier, Oliver Obst, M...
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...
Subspace learning techniques are widespread in pattern recognition research. They include Principal Component Analysis (PCA), Locality Preserving Projection (LPP), etc. These tech...
The POIROT project is a four-year effort to develop an architecture that integrates the products of a number of targeted reasoning and learning components to produce executable re...
Mark H. Burstein, Fusun Yaman, Robert Laddaga, Rob...