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New SMT-based encoding enhances numerical HTN planning capabilities

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new method for numerical Hierarchical Task Network (HTN) planning by extending standard SAT-based encodings with Satisfiability Modulo Theories (SMT). This approach enables the handling of numeric fluents within HTN planning, a capability that has been limited in previous systems. The team has also introduced a benchmark suite to facilitate the evaluation of numerical TOHTN planning, establishing a competitive baseline for future research in this area. AI

IMPACT This research could lead to more expressive and capable AI planning systems by enabling them to reason with numerical constraints.

RANK_REASON The cluster contains an academic paper detailing a new technical approach to a subfield of AI planning. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New SMT-based encoding enhances numerical HTN planning capabilities

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The cluster contains an academic paper detailing a new technical approach to a subfield of AI planning. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Gaspard Quenard, Takudzwa Togarepi, Damien Pellier, Humbert Fiorino ·

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

    arXiv:2609.03938v1 Announce Type: new 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-base…

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