SOURCE-LINKED INTELLIGENCE

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

arXiv · AI, language, vision and robotics · article · Sep 3, 2026 · UTC

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

Read original source ↗ Open in workspace

recordType

paper

region

Global