Structurally Restricted Fragments of Numeric Planning - a Complexity Analysis
Alexander Shleyfman, Daniel Gnad, Peter Jonsson
Abstract
Numeric planning is known to be undecidable even under severe restrictions. Prior work has investigated the decidability boundaries by restricting the expressiveness of the planning formalism in terms of the numeric functions allowed in conditions and effects. We study a well-known restricted form of Hoffmann's simple numeric planning, which is undecidable. We analyze the complexity by imposing restrictions on the causal structure, exploiting a novel method for bounding variable domain sizes. First, we show that plan existence for tasks where all numeric variables are root nodes in the causal graph is in PSPACE. Second, we show that for tasks with only numeric leaf variables the problem is decidable, and that it is in PSPACE if the propositional state space has a fixed size. Our work lays a strong foundation for future investigations of structurally more complex tasks. From a practical perspective, our method allows to employ heuristics and methods that are geared towards finite variable domains (such as pattern database heuristics or decoupled search) to solve non-trivial families of numeric planning problems.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext b2537d84-c8bf-4265-b662-7269d755cb2fCited by top-tier papers3
- Towards Practical Classical Planning Compilations of Numeric PlanningLuigi Bonassi, Francesco Percassi, Enrico ScalaAAAI 2025 · 1 citation
- PDBs Go Numeric: Pattern-Database Heuristics for Simple Numeric PlanningDaniel Gnad, Lee-or Alon, Eyal Weiss, Alexander ShleyfmanAAAI 2025 · 1 citation
- Managing Infinite Abstractions in Numeric Pattern Database HeuristicsMarkus Fritzsche, Daniel Gnad, Mikhail Gruntov, Alexander ShleyfmanAAAI 2026
Related papers
- Learning Heuristic Functions with Graph Neural Networks for Numeric PlanningValerio Borelli, Alfonso Gerevini, Enrico Scala, Ivan SerinaAAAI 2026 · 1 citation
- Symmetries and Other Variations of "End-Recursive" HTN Problems: Mapping the Border Between Decidable and Undecidable RestrictionsHadyn Tang, Pascal BercherAAAI 2026
- Task and Motion Planning Is PSPACE-CompleteWilliam Vega-Brown, Nicholas RoyAAAI 2020 · 10 citations
- On the Computational Complexity of Plan Verification, (Bounded) Plan-Optimality Verification, and Bounded Plan ExistenceSongtuan Lin, Conny Olz, Malte Helmert, Pascal BercherAAAI 2024 · 3 citations
- Counting and Reasoning with PlansDavid Speck, Markus Hecher, Daniel Gnad, Johannes Klaus Fichte et al.AAAI 2025 · 2 citations
