Reinforcement learning (RL) was originally proposed as a framework to allow agents to learn in an online fashion as they interact with their environment. Existing RL algorithms co...
Pascal Poupart, Nikos A. Vlassis, Jesse Hoey, Kevi...
We present a new algorithm, called incremental least squares policy iteration (ILSPI), for finding the infinite-horizon stationary policy for partially observable Markov decision ...
— Target tracking has two variants that are often studied independently with different approaches: target searching requires a robot to find a target initially not visible, and ...
Visual sensors provide exclusively uncertain and partial knowledge of a scene. In this article, we present a suitable scene knowledge representation that makes integration and fusi...
ion in PRISM1 Mark Kattenbelt Marta Kwiatkowska Gethin Norman David Parker Oxford University Computing Laboratory, Oxford, UK Modelling and verification of systems such as communi...
Mark Kattenbelt, Marta Z. Kwiatkowska, Gethin Norm...