To avoid the curse of dimensionality, function approximators are used in reinforcement learning to learn value functions for individual states. In order to make better use of comp...
We introduce the first algorithm for off-policy temporal-difference learning that is stable with linear function approximation. Off-policy learning is of interest because it forms...
The spatio-temporal information of a video object is important for content-based video retrieval. In this paper the spatio-temporal information of a video object, such as the velo...
—In this paper we extend the class of MAP queueing networks to include blocking models, which are useful to describe the performance of service instances which have a limited con...
Vittoria de Nitto Persone, Giuliano Casale, Evgeni...