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...
For the past few years many new applications are being developed featuring interactive environments populated with autonomous virtual agents capable of acting according to their g...
: Models of the association between input accuracy and output accuracy imply that, for any given application, the effect of input errors on the output error rate generally varies i...
Machine learning with few training examples always leads to over-fitting problems, whereas human individuals are often able to recognize difficult object categories from only one ...
Partially observed actions are observations of action executions in which we are uncertain about the identity of objects, agents, or locations involved in the actions (e.g., we kn...