The ability for an agent to reason under uncertainty is crucial for many planning applications, since an agent rarely has access to complete, error-free information about its envi...
Flexible general purpose robots need to tailor their visual processing to their task, on the fly. We propose a new approach to this within a planning framework, where the goal is ...
We study the problem of generating e cient, equivalent rewritings using views to compute the answer to a query. We take the closed-world assumption, in which views are materialize...
Planning under uncertainty involves two distinct sources of uncertainty: uncertainty about the effects of actions and uncertainty about the current state of the world. The most wi...
Decentralized partially observable MDPs (DEC-POMDPs) provide a rich framework for modeling decision making by a team of agents. Despite rapid progress in this area, the limited sc...