Extending Hierarchical Partial-Order Causal-Link Planning to Temporal Problem Solving
Résumé
This paper introduces TEP (Temporal Event Planning), a novel POCL (Partial Ordered Causal Link) HTN approach tailored for temporal Hierarchical Task Networks (HTNs). TEP stands out for its capability to address the three categories of temporal problems as categorized by Cushing, distinguishing it from prevailing approaches that primarily tackle the initial two categories. TEP accomplishes this by translating temporal HTN problems into non-temporal counterparts and excels in performance by leveraging heuristics developed in non-temporal HTN planning to steer the search for temporal solutions. This innovative strategy initiates by refining tasks into instantaneous actions and relaxing duration constraints, ensuring alignment with conventional search heuristics while upholding the problem's innate expressiveness.
Domaines
Intelligence artificielle [cs.AI]Origine | Fichiers produits par l'(les) auteur(s) |
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