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dc.contributor.authorHoffmann, Jörgen_US
dc.date.accessioned2019-05-28T04:16:57Z
dc.date.available2019-05-28T04:16:57Z
dc.date.issued2003en_US
dc.identifier.isbn3540202595en_US
dc.identifier.otherHPU1161382en_US
dc.identifier.urihttps://lib.hpu.edu.vn/handle/123456789/32783
dc.description.abstractPlanning is a crucial skill for any autonomous agent, be it a physically embedded agent, such as a robot, or a purely simulated software agent. For this reason, planning, as a central research area of artificial intelligence from its beginnings, has gained even more attention and importance recently.After giving a general introduction to AI planning, the book describes and carefully evaluates the algorithmic techniques used in fast-forward planning systems (FF), demonstrating their excellent performance in many wellknown benchmark domains. In advance, an original and detailed investigation identifies the main patterns of structure which cause the performance of FF, categorizing planning domains in a taxonomy of different classes with respect to their aptitude for being solved by heuristic approaches, such as FF. As shown, the majority of the planning benchmark domains lie in classes which are easy to solve.en_US
dc.format.extent254 p.en_US
dc.format.mimetypeapplication/pdf
dc.language.isoenen_US
dc.publisherSpringer-Verlag Berlin Heidelbergen_US
dc.subjectArtificial Intelligenceen_US
dc.subjectAlgorithm Analysisen_US
dc.subjectProblem Complexityen_US
dc.titleUtilizing Problem Structure in Planning: A Local Search Approachen_US
dc.typeBooken_US
dc.size2,747 KBen_US
dc.departmentTechnologyen_US


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