Translating Totally Ordered HTN Planning Problems to Classical Planning Problems Using Regular Approximation of Context-Free Languages

Abstract

There have been several approaches to use techniques from classical planning in HTN planning. While a direct translation is in general not possible due to the different expressiveness, there have been translations of bounded HTN problems and approaches to use classical heuristics in HTN search procedures. In this paper, we introduce a different approach. We exploit methods from the field of Computational Linguistics introduced to approximate Context-Free Languages by Finite Automata. We use them to approximate the decomposition structure of Totally Ordered (TO) HTN planning problems by classical problems. The resulting problem can then be solved using standard classical planning systems. A subset of TOHTN problems can be translated exactly, i.e., without changing the set of solutions. For problems where an approximation is necessary, we use an overapproximation, i.e., the set of solutions to the classical problem is a superset of that of the HTN problem. We then use plan verification to check whether a solution is valid and thus obtain a sound and complete overall approach. The resulting system outperforms the state of the art on the IPC 2020 benchmark set in terms of coverage.

The 2023 International Planning Competition

“…Aries (A. Bit‐Monnot), LTP ( Lifted Tree Path ) (G. Quenard, D. Pellier, H. Fiorino), and OptiPlan (O. Firsov, D. Pellier, H. Fiorino) perform planning via constraint programming and/or SAT solving. TOAD Höller (2021) uses a translation to classical planning. Lastly, the submissions Lifted‐Linear , Linear‐Simple , and Linear‐Complex (Y. X. Wu, C. Olz, S. Lin, P. Bercher) perform a preprocessing which linearizes PO into TO problems and then use one of several established TOHTN planners.…”

Loop Detection in the PANDA Planning System

“…We tested against PANDA without our techniques and against the participants of the IPC 2020, i.e., HY-PERTENSION (Magnaguagno, Meneguzzi, and de Silva 2021), LILOTANE (Schreiber 2021a,b), SIADEX (Fernandez-Olivares, Vellido, and Castillo 2021), PDDL4J (Pellier and Fiorino 2021), PYHIPOP (Lesire and Albore 2021). We further included the TOAD system (Höller 2021), and PAN-DASAT in its current TO (Behnke, Höller, and Biundo 2018;Behnke 2021) and PO versions (Behnke, Höller, and Biundo 2019). We have updated the IPC planners to their newest versions, some of which fixed bugs in the original planners.…”

Accelerating SAT-Based HTN Plan Verification by Exploiting Data Structures from HTN Planning

“…Research on this problem has drawn increasing attention in the last few years due to its potential usages in numerous applications, e.g., in mixed initiative planning [6,22], in validating planning domains [19,21,20] where failed plan verification indicates flaws in planning domains, and in International Planning Competition. Recently, there were also attempts to exploit plan verification to solve planning problems [14]. Plan verification is an easy task in classical planning, whereas it is computationally expensive in the hierarchical setting.…”