Sparse coding of sensory data has recently attracted notable attention in research of learning useful features from the unlabeled data. Empirical studies show that mapping the data...
The last few years have seen great maturationin the computation speed and control methods needed to portray 3D virtualhumanssuitableforreal interactiveapplications. We first desc...
In this work, we show the importance of multidimensional opinion representation in the political context combining domain knowledge and results from principal component analysis. ...
Abstract. In the context of situated and embodied cognition, we evaluate an information-theoretic approach to the construction of the Umwelt of an artificial agent. We make the ass...
Philippe Capdepuy, Daniel Polani, Chrystopher L. N...
Factored representations, model-based learning, and hierarchies are well-studied techniques for improving the learning efficiency of reinforcement-learning algorithms in large-sca...
Carlos Diuk, Alexander L. Strehl, Michael L. Littm...