— We are interested in transferring control policies for arbitrary tasks from a human to a robot. Using interactive demonstration via teloperation as our transfer scenario, we ca...
The steadily increasing complexity of embedded systems requires comprehensive methodoloat support the design process from the highest possible abstraction level. In most of the cu...
In this paper we introduce a novel approach to manifold alignment, based on Procrustes analysis. Our approach differs from "semisupervised alignment" in that it results ...
Web2.0 has revolutionized the way we use the Web by opening the doors of collaborative learning and direct communication and making the web an open source for learning and exchangi...
We present an expressive agent design language for reinforcement learning that allows the user to constrain the policies considered by the learning process.The language includes s...