Abstract— This paper reports on our efforts to link an industrial state-of-the-art modelling tool to academic state-of-the-art analysis algorithms. In a nutshell, we enable timed...
er provides new techniques for abstracting the state space of a Markov Decision Process (MDP). These techniques extend one of the recent minimization models, known as -reduction, ...
Abstract— We consider the problem of apprenticeship learning when the expert’s demonstration covers only a small part of a large state space. Inverse Reinforcement Learning (IR...
Abstract— In this paper, we propose a way of achieving optimality in radio resource management (RRM) for heterogeneous networks. We consider a micro or femto cell with two co-loc...
Marceau Coupechoux, Jean Marc Kelif, Philippe Godl...
Abstract. Two main challenges of robot action planning in real domains are uncertain action effects and dynamic environments. In this paper, an instance-based action model is lear...