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Complexity Results for HTN Planning

dc.contributor.authorErol, Kutluhanen_US
dc.contributor.authorHendler, Jamesen_US
dc.contributor.authorNau, Dana S.en_US
dc.description.abstract(Also cross-referenced as ISR-TR-95-10) Most practical work on AI planning systems during the last fifteen years has been based on hierarchical task network (HTN) decomposition, but until now, there has been very little analytical work on the properties of HTN planners. This paper describes how the complexity of HTN planning varies with various conditions on the task networks, and how it compares to STRIPS-style planning. (Also cross-referenced as UMIACS-TR-94-32)en_US
dc.format.extent297526 bytes
dc.relation.ispartofseriesUM Computer Science Department; CS-TR-3240en_US
dc.relation.ispartofseriesUMIACS; UMIACS-TR-94-32en_US
dc.titleComplexity Results for HTN Planningen_US
dc.typeTechnical Reporten_US
dc.relation.isAvailableAtDigital Repository at the University of Marylanden_US
dc.relation.isAvailableAtUniversity of Maryland (College Park, Md.)en_US
dc.relation.isAvailableAtTech Reports in Computer Science and Engineeringen_US
dc.relation.isAvailableAtUMIACS Technical Reportsen_US

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