Landmark Extraction in HTN Planning

Landmarks are state features that need to be made true or tasks that need to be contained in every solution of a planning problem. They are a valuable source of information in planning and can be exploited in various ways. Landmarks have been used both in classical and hierarchical planning, but while there is much work in classical planning, the techniques in hierarchical planning are less evolved. In this paper we introduce a novel landmark generation method for Hierarchical Task Network (HTN) planning and show that it is sound and incomplete.We show that every complete approach is as hard as the underlying HTN problem. Since we make relaxations during landmark generation, this means NP-hard for our setting (while our approach is in P). On a widely used benchmark set, our approach finds more than twice the number of landmarks than the approach from the literature. Though our focus is on landmark generation, we show that the newly discovered landmarks bear information beneficial for solvers.