dc.contributor.author | Erol, Kutluhan | en_US |
dc.contributor.author | Hendler, James | en_US |
dc.contributor.author | Nau, Dana S. | en_US |
dc.date.accessioned | 2004-05-31T22:25:38Z | |
dc.date.available | 2004-05-31T22:25:38Z | |
dc.date.created | 1994-03 | en_US |
dc.date.issued | 1998-10-15 | en_US |
dc.identifier.uri | http://hdl.handle.net/1903/625 | |
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.extent | 297526 bytes | |
dc.format.mimetype | application/postscript | |
dc.language.iso | en_US | |
dc.relation.ispartofseries | UM Computer Science Department; CS-TR-3240 | en_US |
dc.relation.ispartofseries | ISR-TR-95-10 | en_US |
dc.relation.ispartofseries | UMIACS; UMIACS-TR-94-32 | en_US |
dc.title | Complexity Results for HTN Planning | en_US |
dc.type | Technical Report | en_US |
dc.relation.isAvailableAt | Digital Repository at the University of Maryland | en_US |
dc.relation.isAvailableAt | University of Maryland (College Park, Md.) | en_US |
dc.relation.isAvailableAt | Tech Reports in Computer Science and Engineering | en_US |
dc.relation.isAvailableAt | UMIACS Technical Reports | en_US |