Abstract. Learning to act in an unknown partially observable domain is a difficult variant of the reinforcement learning paradigm. Research in the area has focused on model-free m...
Just as actions can have indirect effects on the state of the world, so too can sensing actions have indirect effects on an agent's state of knowledge. In this paper, we inve...
Autonomous robots, such as automatic vacuum cleaners, toy robot dogs, and autonomous vehicles for the military, are rapidly becoming a part of everyday life. As a result the need ...
This paper proposes a fast 3D reconstruction approach for efficiently generating watertight 3D models from multiple short baseline views. Our method is based on the combination of...
Mario Sormann, Christopher Zach, Joachim Bauer, Ko...
Multiagent learning can be seen as applying ML techniques to the core issues of multiagent systems, like communication, coordination, and competition. In this paper, we address the...