Opposed to linear schemes, nonlinear function approximation allows to obtain a dimension independent rate of convergence. Unfortunately, in the presence of data noise typical algo...
In this paper, we present an approach for learning interest profiles implicitly from positive user observations only. This approach eliminates the need to prompt users for ratings...
In an open distributed system, computational resources are peer-owned, and distributed over time and space. The fact that these resources can dynamically join or leave the system (...
This paper proposes a support tool for designers who have realized the potential benefits of using a scenario-based approach, yet need a more concrete guidance for its implementati...
Abstract-- We consider reinforcement learning, and in particular, the Q-learning algorithm in large state and action spaces. In order to cope with the size of the spaces, a functio...