Learning function relations or understanding structures of data lying in manifolds embedded in huge dimensional Euclidean spaces is an important topic in learning theory. In this ...
nizing multiple forms of information and knowledge processing on different levels of abstraction in a structured and principled manner. We propose knowledge processing middleware a...
It is well known that classical set theory is not expressive enough to adequately model categorization and prototype theory. Recent work on compositionality and concept determinat...
Abstract— Robot imitation is a useful and promising alternative to robot programming. Robot imitation involves two crucial issues. The first is how a robot can imitate a human w...
Ryunosuke Yokoya, Tetsuya Ogata, Jun Tani, Kazunor...
This paper addresses planning of continuous paths for mobile sensors to reduce uncertainty in some quantities of interest in the future. The mutual information between the measure...