How Good is Perfect? On the Incompleteness of A* for Total-Order HTN Planning

This paper reveals the inherent limitations of A* in HTN planning by identifying various cycle types induced by the task hierarchy and analyzing their effects on the termination of the algorithm. We prove that A* even with the perfect heuristic, and for the special case of totally ordered problems, which are known to be decidable, is incomplete. An especially interesting results is that having a visited list (i.e., graph search) with the null heuristic has better termination guarantees than tree search with the perfect heuristic. We provide a polynomial-time test for detecting those cycles that render A* incomplete, and analyzed all existing benchmark domains from the most-recent international planning competition. Results show that in more than half of all domains, A* tree search would be incomplete even with the perfect heuristic, and in roughly 40% of cases A* graph search might also be incomplete depending on the provided heuristic function. We also point to a normal form that preserves semantics and guarantees completeness of the resulting models, though implementation and testing remains for future work.

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Publication Details

Journal
Proceedings of the International Conference on Automated Planning and Scheduling
Published
2025-09-16
DOI
https://doi.org/10.1609/icaps.v35i1.36107
Primary Topic
Petri Nets in System Modeling
Type
article
Field-Weighted Citation Impact
0.00

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article

How Good is Perfect? On the Incompleteness of A* for Total-Order HTN Planning

Pascal Bercher, Mario Schmautz, Patrik Haslum, Mohammad Yousefi
Proceedings of the International Conference on Automated Planning and Scheduling
Petri Nets in System Modeling
article

How Good is Perfect? On the Incompleteness of A* for Total-Order HTN Planning

Pascal Bercher, Mario Schmautz, Patrik Haslum, Mohammad Yousefi
article en

Abstract

This paper reveals the inherent limitations of A* in HTN planning by identifying various cycle types induced by the task hierarchy and analyzing their effects on the termination of the algorithm. We prove that A* even with the perfect heuristic, and for the special case of totally ordered problems, which are known to be decidable, is incomplete. An especially interesting results is that having a visited list (i.e., graph search) with the null heuristic has better termination guarantees than tree search with the perfect heuristic. We provide a polynomial-time test for detecting those cycles that render A* incomplete, and analyzed all existing benchmark domains from the most-recent international planning competition. Results show that in more than half of all domains, A* tree search would be incomplete even with the perfect heuristic, and in roughly 40% of cases A* graph search might also be incomplete depending on the provided heuristic function. We also point to a normal form that preserves semantics and guarantees completeness of the resulting models, though implementation and testing remains for future work.

Proceedings of the International Conference on Automated Planning and SchedulingVol. 35(1)
Australian National University (AU)
Australian Government
Openalex Percentile: Top 74%
Petri Nets in System Modeling
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