Landmark-Based Plan Recognition
  Recognition of goals and plans using incomplete evidence from action
execution can be done efficiently by using planning techniques. In many
applications it is important to recognize goals and plans not only accurately,
but also quickly. In this paper, we develop a heuristic approach for
recognizing plans based on planning techniques that rely on ordering
constraints to filter candidate goals from observations. These ordering
constraints are called landmarks in the planning literature, which are facts or
actions that cannot be avoided to achieve a goal. We show the applicability of
planning landmarks in two settings: first, we use it directly to develop a
heuristic-based plan recognition approach; second, we refine an existing
planning-based plan recognition approach by pre-filtering its candidate goals.
Our empirical evaluation shows that our approach is not only substantially more
accurate than the state-of-the-art in all available datasets, it is also an
order of magnitude faster.
