We introduce a novel data-driven mean-shift belief propagation
(DDMSBP) method for non-Gaussian MRFs, which
often arise in computer vision applications. With the aid
of scale sp...
— Partially Observable Markov Decision Processes (POMDPs) provide a rich mathematical model to handle realworld sequential decision processes but require a known model to be solv...
This paper proposes a formally well-rooted and extensible framework for dependability evaluation: Arcade (architectural dependability evaluation). It has been designed to combine ...
Hichem Boudali, Pepijn Crouzen, Boudewijn R. Haver...
Representing and Reasoning about time and change is one of the primary issues in the area of Artificial Intelligence (AI) and Knowledge Representation (KR). Despite the importance...
Abstract— Sampling-based algorithms have dramatically improved the state of the art in robotic motion planning. However, they make restrictive assumptions that limit their applic...