Abstract— We consider the problem of apprenticeship learning when the expert’s demonstration covers only a small part of a large state space. Inverse Reinforcement Learning (IR...
—We are concerned with enabling truly large scale autonomous navigation in typical human environments. To this end we describe the acquisition and modeling of large urban spaces ...
Gabe Sibley, Christopher Mei, Ian D. Reid, Paul M....
Abstract— This paper presents a geometry-based, multilayered synergistic approach to solve motion planning problems for mobile robots involving temporal goals. The temporal goals...
We attack the task of predicting which news-stories are more appealing to a given audience by comparing ‘most popular stories’, gathered from various online news outlets, over ...
Elena Hensinger, Ilias N. Flaounas, Nello Cristian...
Abstract—Existing work on cross-layer optimization for wireless networks adopts simple physical-layer models, i.e., treating interference as noise. In this paper, we adopt a dete...