On the Use of Integer Programming Models in AI Planning

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dc.contributor.authorVossen, Thomasen_US
dc.contributor.authorBall, Michael O.en_US
dc.contributor.authorLotem, Amnonen_US
dc.contributor.authorNau, Danaen_US
dc.contributor.departmentISRen_US
dc.date.accessioned2007-05-23T10:07:35Z
dc.date.available2007-05-23T10:07:35Z
dc.date.issued1999en_US
dc.description.abstractRecent research has shown the promise of using propositional reasoning and search to solve AI planning problems. In this paper, we further explore this area by applying Integer Programming to solve AI planning problems. The application of Integer Programming to AI planning has a potentially significant advantage, as it allows quite naturally for the incorporation of numerical constraints and objectives into the planning domain. Moreover, the application of Integer Programming to AI planning addresses one of the challenges in propositional reasoning posed by Kautz and Selman, who conjectured that the principal technique used to solve Integer Programs---the linear programming (LP) relaxation---is not useful when applied to propositional search. We discuss various IP formulations for the class of planning problems based on the STRIPS paradigm. Our main objective is to show that a carefully chosen IP formulation significantly improves the "strength" of the LP relaxation, and that the resultant LPs are useful in solving the IP and the associated planning problems. Our results clearly show the importance of choosing the "right" representation, and more generally the promise of using Integer Programming techniques in the AI planning domain.en_US
dc.format.extent191383 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/1903/6041
dc.language.isoen_USen_US
dc.relation.ispartofseriesISR; TR 1999-84en_US
dc.subjectASIC supporting multiple modulationen_US
dc.subjectdata-aided (DA) estimatorsen_US
dc.subjectQPSK/OQPSK burst modemsen_US
dc.subjectCramer-Rao lower bound (CRLB)en_US
dc.subjectGlobal Communication Systemsen_US
dc.titleOn the Use of Integer Programming Models in AI Planningen_US
dc.typeTechnical Reporten_US

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