Abstract. We present a new reinforcement learning approach for deterministic continuous control problems in environments with unknown, arbitrary reward functions. The difficulty of...
Abstract. Isomap is a highly popular manifold learning and dimensionality reduction technique that effectively performs multidimensional scaling on estimates of geodesic distances....
Modeling tasks, such as surface deformation and editing, can be analyzed by observing the local behavior of the surface. We argue that defining a modeling operation by asking for ...
Emergence is a concept that is not easy to grasp, since it contradicts our idea of central control and planning. In this work, we use a swarm of robots as a tangible tool to visua...
Principles of the framework called time series forecasting automation are presented. It is required in processing massive temporal data sets and creating completely user-oriented f...