Active Goal Recognition
  To coordinate with other systems, agents must be able to determine what the
systems are currently doing and predict what they will be doing in the
future---plan and goal recognition. There are many methods for plan and goal
recognition, but they assume a passive observer that continually monitors the
target system. Real-world domains, where information gathering has a cost
(e.g., moving a camera or a robot, or time taken away from another task), will
often require a more active observer. We propose to combine goal recognition
with other observer tasks in order to obtain \emph{active goal recognition}
(AGR). We discuss this problem and provide a model and preliminary experimental
results for one form of this composite problem. As expected, the results show
that optimal behavior in AGR problems balance information gathering with other
actions (e.g., task completion) such as to achieve all tasks jointly and
efficiently. We hope that our formulation opens the door for extensive further
research on this interesting and realistic problem.
