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dc.contributor.authorNau, D.S.en_US
dc.contributor.authorGupta, Sandeep K.en_US
dc.contributor.authorRegli, W.C.en_US
dc.date.accessioned2007-05-23T09:59:06Z
dc.date.available2007-05-23T09:59:06Z
dc.date.issued1995en_US
dc.identifier.urihttp://hdl.handle.net/1903/5636
dc.description.abstractAlthough AI planning techniques can potentially be useful in several manufacturing domains, this potential remains largely unrealized. In order to adapt AI planning techniques to manufacturing, it is important to develop more realistic and robust ways to address issues important to manufacturing engineers. Furthermore, by investigating such issues, AI researchers may be able to discover principles that are relevant for AI planning in general. As an example, in this paper we describe the techniques for manufacturing-operation planning used in IMACS (Interactive Manufacturability Analysis and Critiquing System), and compare and contrast them with the techniques used in classical AI planning systems. We describe how one of IMACS's planning techniques may be useful for AI planning in general -- and as an example, we describe how it helps to explain a puzzling complexity result in AI planning.en_US
dc.format.extent727543 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen_USen_US
dc.relation.ispartofseriesISR; TR 1995-48en_US
dc.subjectcomputational complexityen_US
dc.subjectcomputational geometryen_US
dc.subjectexpert systemsen_US
dc.subjectcomputer aided manufacturingen_US
dc.subjectcomputer integrated manufacturingen_US
dc.subjectmanufacturingen_US
dc.subjectsolid modelingen_US
dc.subjectAI planningen_US
dc.subjectSystems Integration Methodologyen_US
dc.titleAI Planning Versus Manufacturing-Operation Planning: A Case Studyen_US
dc.typeTechnical Reporten_US
dc.contributor.departmentISRen_US


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