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HDDL: An Extension to PDDL for Expressing Hierarchical Planning Problems

Daniel Höller, Gregor Behnke, Pascal Bercher, Susanne Biundo, Humbert Fiorino, Damien Pellier, Ron Alford

2020Proceedings of the AAAI Conference on Artificial Intelligence69 citationsDOIOpen Access PDF

Abstract

The research in hierarchical planning has made considerable progress in the last few years. Many recent systems do not rely on hand-tailored advice anymore to find solutions, but are supposed to be domain-independent systems that come with sophisticated solving techniques. In principle, this development would make the comparison between systems easier (because the domains are not tailored to a single system anymore) and – much more important – also the integration into other systems, because the modeling process is less tedious (due to the lack of advice) and there is no (or less) commitment to a certain planning system the model is created for. However, these advantages are destroyed by the lack of a common input language and feature set supported by the different systems. In this paper, we propose an extension to PDDL, the description language used in non-hierarchical planning, to the needs of hierarchical planning systems.

Topics & Concepts

Computer scienceExtension (predicate logic)Domain (mathematical analysis)Set (abstract data type)Process (computing)Advice (programming)Feature (linguistics)Business system planningModeling languageSoftware engineeringArtificial intelligenceProcess managementManagement scienceProgramming languageEngineeringLinguisticsMathematicsMathematical analysisSoftwarePhilosophyAI-based Problem Solving and PlanningModel-Driven Software Engineering TechniquesSemantic Web and Ontologies
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