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This paper investigates numerical Totally-Ordered HTN planning by extending SAT-based encodings with SMT to handle numeric fluents, introduces a benchmark suite, and shows competitive performance as a baseline for future work.
This paper adapts two plan deordering techniques from classical planning to hierarchical task network planning, showing a substantial reduction in ordering constraints while maintaining plan validity.