Event date · · arXiv

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

FACT STATEMENT

A paper titled 'Towards Numerical TOHTN Planning with SMT-based HTN-SAT Encoding' was published on arXiv on 2026-09-03. It investigates numerical Totally-Ordered HTN (TOHTN) planning and extends standard SAT-based encodings with SMT to handle numeric fluents. The paper introduces a benchmark suite for numerical TOHTN planning and reports experimental results showing the encoding is a competitive baseline.

What happened

The paper addresses the limited support for numerical reasoning in HTN planning by proposing an SMT-based extension of SAT encodings for numerical Totally-Ordered HTN planning. It also provides a new benchmark suite for evaluation in this setting. Experimental results indicate that the simple encoding is competitive, opening the way for more expressive HTN planning approaches.

Technical significance

The approach extends SAT-based HTN encodings with SMT to handle numeric fluents, enabling reasoning over numerical constraints in totally-ordered HTN planning. The introduction of a benchmark suite provides a common evaluation basis, and the competitive baseline suggests that SMT-based encodings are a viable starting point for numerical HTN planning.

Industry impact

This research may influence automated planning systems that require numerical reasoning, such as logistics, robotics, and resource management. The benchmark suite could become a standard for evaluating numerical HTN planners, potentially guiding future tool development.

Decision value

The paper provides a foundation for developing planning systems that handle numerical constraints, which could be valuable in industries requiring complex task planning with resource or metric considerations.

What to watch

Future work may explore more expressive encodings and optimizations for numerical HTN planning. The benchmark suite may be adopted by the planning community, leading to comparative studies and improvements in planner performance.

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