Abstract
Planning is the task of finding a sequence of actions
that achieves the goal(s) of an agent. It is solved
based on a model describing the environment and
how to change it. There are several approaches
to solve planning tasks, two of the most popular
are classical planning and hierarchical planning.
Solvers are often based on heuristic search, but especially regarding domain-independent heuristics,
techniques in classical planning are more sophisticated. However, due to the different problem
classes, it is difficult to use them in hierarchical
planning. In this paper we describe how to use arbitrary classical heuristics in hierarchical planning
and show that the resulting system outperforms the
state of the art in hierarchical planning