In this paper, we address the problem of generating preferred plans by
combining the procedural control knowledge specified by Hierarchical Task
Networks (HTNs) with rich qualitative user preferences. The outcome of our work
is a language for specifyin user preferences, tailored to HTN planning,
together with a provably optimal preference-based planner, HTNPLAN, that is
implemented as an extension of SHOP2. To compute preferred plans, we propose an
approach based on forward-chaining heuristic search.