POMDPs are the models of choice for reinforcement learning (RL) tasks where the environment cannot be observed directly. In many applications we need to learn the POMDP structure ...
— We present a novel approach for determining robot movements that efficiently accomplish the robot’s tasks while not hindering the movements of people within the environment....
Brian Ziebart, Nathan D. Ratliff, Garratt Gallaghe...
This paper examines the problem of finding an optimal policy for a Partially Observable Markov Decision Process (POMDP) when the model is not known or is only poorly specified. W...
Large scale Open Systems are built from reusable components in such a way that enhanced system functionality can be deployed, quickly and effectively, simply by plugging in a few n...
Large, complex projects face significant barriers to coordination and communication due to continuous, rapid changes during a project's lifecycle. Such changes must be tracke...