A large variety of communication systems, including telephone and data networks, can be represented by so-called Whittle networks. The stationary distribution of these networks is...
Thomas Bonald, Matthieu Jonckheere, Alexandre Prou...
In a typical reinforcement learning (RL) setting details of the environment are not given explicitly but have to be estimated from observations. Most RL approaches only optimize th...
Partially Observable Markov Decision Process models (POMDPs) have been applied to low-level robot control. We show how to use POMDPs differently, namely for sensorplanning in the ...
This paper describes a statistically motivated framework for performing real-time dialogue state updates and policy learning in a spoken dialogue system. The framework is based on...
Traditional studies of routing problems often assumed strict preferences on paths, by eliminating ambiguity in path comparisons, or imposing a priori deterministic tie-breaking. S...