We describe and evaluate a system for learning domainspecific control knowledge. In particular, given a planning domain, the goal is to output a control policy that performs well ...
Maximum a posteriori (MAP) filtering using the HuberMarkov random field (HMRF) image model has been shown in the past to be an effective method of reducing compression artifacts i...
This work presents a novel approach to object localization in complex imagery. In particular, the spatial extents of objects characterized by distinct spatial signatures at multip...
As a general framework to determine a collision-free feedback motion strategies, the Random Neighborhood Graph (RNG) approach [19] defines a global navigation function over an ap...
This paper closes a gap in the foundations of the theory of average case complexity. First, we clarify the notion of a feasible solution for a search problem and prove its robustne...