Abstract--The problem of state estimation with initial state uncertainty is approached from a statistical decision theory point of view. The initial state is regarded as determinis...
Most of current machine vision systems suffer from a lack of flexibility to account for the high variability of unstructured environments. Here, as the state of the world evolves ...
Ellipsoidal outer-bounding of the set of all feasible state vectors under model uncertainty is a natural extension of state estimation for deterministic models with unknown-but-bo...
Reinforcement learning models generally assume that a stimulus is presented that allows a learner to unambiguously identify the state of nature, and the reward received is drawn f...
Tobias Larsen, David S. Leslie, Edmund J. Collins,...