We state the problem of inverse reinforcement learning in terms of preference elicitation, resulting in a principled (Bayesian) statistical formulation. This generalises previous w...
We consider the task of reinforcement learning in an environment in which rare significant events occur independently of the actions selected by the controlling agent. If these ev...
This paper investigates the problem of automatically learning how to restructure the reward function of a Markov decision process so as to speed up reinforcement learning. We begi...
— This paper proposes a two-layer Joint Radio Resource Management (JRRM) framework to improve the efficiency in multi-radio and multi-operator cellular scenarios. On the one hand...
This paper investigates how innovation of ICT based services takes place within existing infrastructures, including the whole network of technology, vendors and customers. Our res...