We study how best to schedule scans of large data files, in the presence of many simultaneous requests to a common set of files. The objective is to maximize the overall rate of p...
Even the best laid plans can fail, and robot plans executed in real world domains tend to do so often. The ability of a robot to reliably monitor the execution of plans and detect...
Abdelbaki Bouguerra, Lars Karlsson, Alessandro Saf...
Increasing scale, dynamism, and complexity of hybrid grids make traditional grid resource scheduling approaches difficult. In such grids, where resource volatility and dynamism is...
We consider model-based reinforcement learning in finite Markov Decision Processes (MDPs), focussing on so-called optimistic strategies. Optimism is usually implemented by carryin...
— A new method is presented to test dynamic parameters of Analogue-to-Digital Converters (ADC). A noisy and nonlinear pulse is applied as the test stimulus, which is suitable for...