Despite the recent resurgence of interest in learning methods for planning, most such efforts are still focused exclusively on classical planning problems. In this work, we invest...
We propose a direct reconstruction algorithm for Computed Tomography, based on a local fusion of a few preliminary image estimates by means of a non-linear fusion rule. One such ru...
We investigate the problem of learning action effects in partially observable STRIPS planning domains. Our approach is based on a voted kernel perceptron learning model, where act...
Learning how to make decisions in a domain is a critical aspect of intelligent planning behavior. The ability of a planner to adapt its decision-making to a domain depends in part...
Most of today’s course generation does not allow an in-depth, generic representation of pedagogical knowledge. However, supporting individual learners with different goals requi...