We consider the problem of multi-task reinforcement learning, where the agent needs to solve a sequence of Markov Decision Processes (MDPs) chosen randomly from a fixed but unknow...
Aaron Wilson, Alan Fern, Soumya Ray, Prasad Tadepa...
Distributed applications that can adapt at runtime to changing quality of service (QoS) require a model of the expected QoS and of the possible application adaptations. QoS models ...
DIET (Distributed Interactive Engineering Toolbox) is a set of hierarchical components to design Network Enabled Server (NES) systems. In these systems, clients ask to agents (dis...
We propose a novel unsupervised learning framework for activity perception. To understand activities in complicated scenes from visual data, we propose a hierarchical Bayesian mod...
Grids allow large scale resource-sharing across different administrative domains. Those diverse resources are likely to join or quit the Grid at any moment or possibly to break dow...
Francesc Guim, Ivan Rodero, M. Tomas, Julita Corba...