A Structural Complexity Analysis of Hierarchical Task Network Planning
Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence. Main Track. Pages 4391-4400.
https://doi.org/10.24963/ijcai.2025/489
Keywords
- Planning and Scheduling: PS: Hierarchical planning
- Planning and Scheduling: PS: Theoretical foundations of planning
- Knowledge Representation and Reasoning: KRR: Computational complexity of reasoning
Abstract
We perform a refined complexity-theoretic analysis of three classical problems in the context of Hierarchical Task Network Planning: the verification of a provided plan, whether an executable plan exists, and whether a given state can be reached. Our focus lies on identifying structural properties which yield tractability. We obtain new polynomial algorithms for all three problems on a natural class of primitive networks, along with corresponding lower bounds. We also obtain an algorithmic meta-theorem for lifting polynomial-time solvability from primitive to general task networks, and prove that its preconditions are tight. Finally, we analyze the parameterized complexity of the three problems.
@inproceedings{ijcai2025p489,
title = {A Structural Complexity Analysis of Hierarchical Task Network Planning},
author = {Brand, Cornelius and Ganian, Robert and Mc Inerney, Fionn and Wietheger, Simon},
booktitle = {Proceedings of the Thirty-Fourth International Joint Conference on
Artificial Intelligence, {IJCAI-25}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {James Kwok},
pages = {4391--4400},
year = {2025},
month = {8},
note = {Main Track},
doi = {10.24963/ijcai.2025/489},
url = {https://doi.org/10.24963/ijcai.2025/489},
}
TY - CPAPER TI - A Structural Complexity Analysis of Hierarchical Task Network Planning AU - Brand, Cornelius AU - Ganian, Robert AU - Mc Inerney, Fionn AU - Wietheger, Simon T2 - Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-25 PB - International Joint Conferences on Artificial Intelligence Organization PY - 2025 SP - 4391 EP - 4400 DO - 10.24963/ijcai.2025/489 UR - https://doi.org/10.24963/ijcai.2025/489 ER -Copied
Machine-readable versions of this paper, for tools and AI agents: