Factored representations, model-based learning, and hierarchies are well-studied techniques for improving the learning efficiency of reinforcement-learning algorithms in large-sca...
Carlos Diuk, Alexander L. Strehl, Michael L. Littm...
Ad hoc networks are a type of computational system whose members may fail to, or choose not to, comply with the laws governing their behaviour. We are investigating to what extent ...
We consider the two-fold problem of representing collective beliefs and aggregating these beliefs. We propose a novel representation for collective beliefs that uses modular, tran...
The popularity of current hand-held digital imaging devices such as camera phones, PDAs, camcorders has promoted the use of digital cameras to capture document images for daily in...
This paper deals with the monitoring and diagnosis of large discrete-event systems. The problem is to determine, online, all faults and states that explain the flow of observatio...