The existing reinforcement learning approaches have been suffering from the curse of dimension problem when they are applied to multiagent dynamic environments. One of the typical...
The different ways in which concepts within computer networks are understood by master level students who take an internationally distributed project-based course have been identi...
— Estimating the pose of an imaging sensor is a central research problem. Many solutions have been proposed for the case of a rigid environment. In contrast, we tackle the case o...
We address the problem of reinforcement learning in which observations may exhibit an arbitrary form of stochastic dependence on past observations and actions. The task for an age...
Improving the sample efficiency of reinforcement learning algorithms to scale up to larger and more realistic domains is a current research challenge in machine learning. Model-ba...