This paper describes an experiment performed on Wide Area Network to assess and fairly compare the Quality of Service provided by a large family of failure detectors. Failure dete...
Particle filters (PFs) are powerful samplingbased inference/learning algorithms for dynamic Bayesian networks (DBNs). They allow us to treat, in a principled way, any type of prob...
Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, ...
In this paper the application of reinforcement learning to Tetris is investigated, particulary the idea of temporal difference learning is applied to estimate the state value funct...
The performance skeleton of an application is a short running program whose performance in any scenario reflects the performance of the application it represents. Specifically, th...
Wireless sensor networks have been proposed for many location-dependent applications. In such applications, the requirement of low system cost prohibits many range-based methods f...