Existing value function approximation methods have been successfully used in many applications, but they often lack useful a priori error bounds. We propose a new approximate bili...
—We consider the problem of ’fair’ scheduling the resources to one of the many mobile stations by a centrally controlled base station (BS). The BS is the only entity taking d...
Veeraruna Kavitha, Eitan Altman, Rachid El Azouzi,...
Research in efficient methods for solving infinite-horizon MDPs has so far concentrated primarily on discounted MDPs and the more general stochastic shortest path problems (SSPs...
Andrey Kolobov, Mausam, Daniel S. Weld, Hector Gef...
This paper is about Reinforcement Learning (RL) applied to online parameter tuning in Stochastic Local Search (SLS) methods. In particular a novel application of RL is considered i...
tnesses for Abstract Interpretation-based Proofs Fr´ed´eric Besson, Thomas Jensen, and Tiphaine Turpin IRISA/{Inria, CNRS, Universit´e de Rennes 1} Campus de Beaulieu, F-35042 R...