A Hierarchical Structure For Finite Horizon Dynamic Programming Problems

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dc.contributor.advisorBaras, John S.en_US
dc.contributor.authorZhang, Changen_US
dc.contributor.authorBaras, John S.en_US
dc.contributor.departmentISRen_US
dc.contributor.departmentCSHCNen_US
dc.date.accessioned2007-05-23T10:10:12Z
dc.date.available2007-05-23T10:10:12Z
dc.date.issued2000en_US
dc.description.abstractIn dynamic programming (Markov decision) problems, hierarchicalstructure (aggregation) is usually used to simplify computation. Most research on aggregation ofMarkov decision problems is limited to the infinite horizon case, which has good tracking ability. However, in reallife, finite horizon stochastic shortest path problems are oftenencountered. <p>In this paper, we propose a hierarchical structure to solve finite horizon stochastic shortest pathproblems in parallel. In general, the approach reducesthe time complexity of the original problem to a logarithm level, which hassignificant practical meaning.en_US
dc.format.extent251254 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/1903/6175
dc.language.isoen_USen_US
dc.relation.ispartofseriesISR; TR 2000-53en_US
dc.relation.ispartofseriesCSHCN; TR 2000-19en_US
dc.subjectalgorithmsen_US
dc.subjectcomputational complexityen_US
dc.subjectparallel architecturesen_US
dc.subjectclusteringen_US
dc.subjectHierarchical structureen_US
dc.subjectaggregationen_US
dc.subjectdynamic programmingen_US
dc.subjectfinite horizonen_US
dc.subjectstochastic shortest path,en_US
dc.titleA Hierarchical Structure For Finite Horizon Dynamic Programming Problemsen_US
dc.typeTechnical Reporten_US

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