Towards Numerical TOHTN Planning with SMT-based HTN-SAT Encoding

Abstract:While HTN planning has received significant attention in recent years, support for numerical reasoning remains very limited. In this paper, we investigate numerical Totally-Ordered HTN (TOHTN) planning and show how standard SAT-based encodings can be naturally extended with SMT to handle numeric fluents. In addition, we introduce a benchmark suite for numerical TOHTN planning, providing a first common basis for evaluation in this setting. Experimental results show that this simple encoding already constitutes a competitive baseline. This work opens the way to more expressive approaches to HTN planning.

Artificial Intelligence (cs.AI)

arXiv:2609.03938 [cs.AI]

(or arXiv:2609.03938v1 [cs.AI] for this version)

https://doi.org/10.48550/arXiv.2609.03938 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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