Planning in Answer Set Programming Using Ordered Task Decomposition

In this paper we investigate a formalism for solving planning problems based on ordered task decomposition using Answer Set Programming (ASP). Our planning methodology is an adaptation of Hierarchical Task Network (HTN) planning, an approach that has led to some very efficient planners. The ASP paradigm evolved out of the stable semantics for logic programs in recent years and is strongly related to nonmonotonic logics. It also led to various very efficient implementations (Smodels, DLV ). While all previous approaches for using ASP for planning rely on action-based planning, we consider for the first time a formulation of HTN planning as described in the SHOP planning system and define a systematic translation method from SHOP’s representation of a planning problem into a logic program with negation. We show that our translation is sound and complete: answer sets of the logic program obtained by our translation correspond exactly to the solutions of the planning problem. Our approach does not rely on a particular system for computing answer sets and serves several purposes. (1) It constitutes a means to evaluate ASP systems by using well-established benchmarks from the planning community. (2) It makes the more expressive HTN planning available in ASP. (3) When our approach is implemented on ASP solvers, its time requirement appears to grow no faster than roughly proportional to that of a dedicated HTN planning system (SHOP). (4) It outperforms the transformation of an STRIPS-style planning problem into ASP proposed in [Son et al., 2001]. The particular relevance of that transformation method to our work is that, in their work, [Son et al., 2001] proposed to use a form of control knowledge to speed up the classical planning process. In this paper, we show that HTN control knowledge provides more time-efficient transformations compared to the control strategies presented in [Son et al., 2001]. 1Authors’ addresses: Jürgen Dix, Technical University of Clausthal, Institut für Informatik, Julius-Albert-Str. 4, D–38678 Clausthal, Germany. Ugur Kuter and Dana Nau, University of Maryland, Dept. of CS, College Park, MD