HTN Plan Verification by Qualitative Temporal Reasoning

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Authors: Association for Artificial Intelligence 2026, Tobias Schwartz, Diedrich Wolter
Cited by: 0

Abstract

Plan verification is the task of checking whether a proposed plan correctly solves a given planning problem. In Hierarchical Task Network (HTN) planning, this verification problem is known to be NP-complete, even in the grounded setting. Existing approaches to HTN plan verification range from SAT encodings to parser-based techniques. However, the temporal structure that emerges from hierarchical decomposition has not yet been used explicitly as a basis for verification. In this paper, we establish a formal connection between HTN planning and temporal reasoning by showing how decomposition structures can be naturally represented using qualitative constraint networks. Building on this insight, we present a new top-down encoding that transforms the verification of partially ordered task networks into a temporal reasoning problem. We prove the correctness of this encoding and explain how it accounts for both the hierarchical and temporal aspects of HTN plans. By linking HTN plan verification with qualitative temporal reasoning, our approach introduces a principled formal framework for reasoning about complex temporal relationships in hierarchical plans. This connection offers new perspectives for knowledge representation in structured planning domains.

Fields of Study & Subjects

AI-based Problem Solving and Planning Constraint Satisfaction and Optimization Logic Reasoning and Knowledge

Publication details

Journal / source
Underline Science Inc.
Publication date
7 January 2026
Language
EN