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Reachability analysis for uncertain SSPs

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dc.contributor.authorBuffet, Olivier
dc.date.accessioned2015-12-13T23:05:11Z
dc.date.available2015-12-13T23:05:11Z
dc.date.issued2005
dc.date.updated2015-12-12T07:59:06Z
dc.description.abstractStochastic Shortest Path problems (SSPs) can be efficiently dealt with by the Real-Time Dynamic Programming algorithm (RTDP). Yet, RTDP requires that a goal state is always reachable. This paper presents an algorithm checking for goal reachability, especially in the complex case of an uncertain SSP where only a possible interval is known for each transition probability. This gives an analysis method for determining if SSP algorithms such as RTDP are applicable, even if the exact model is not known. We aim at a symbolic analysis in order to avoid a complete state-space enumeration.
dc.identifier.isbn0769524885
dc.identifier.urihttp://hdl.handle.net/1885/85410
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE Inc)
dc.relation.ispartofTools with Artificial Intelligence
dc.relation.isversionof1 Edition
dc.subjectKeywords: Algorithms; Problem solving; Real time systems; State space methods; Real-Time Dynamic Programming algorithm (RTDP); Stochastic Shortest Path problems (SSP); Transition probability; Uncertain systems
dc.titleReachability analysis for uncertain SSPs
dc.typeBook chapter
local.bibliographicCitation.lastpage522
local.bibliographicCitation.placeofpublicationLos Alamitos CA, USA
local.bibliographicCitation.startpage515
local.contributor.affiliationBuffet, Olivier, College of Engineering and Computer Science, ANU
local.contributor.authoruidBuffet, Olivier, a202543
local.description.notesImported from ARIES
local.description.refereedYes
local.identifier.absfor080199 - Artificial Intelligence and Image Processing not elsewhere classified
local.identifier.ariespublicationMigratedxPub13788
local.identifier.doi10.1109/ICTAI.2005.106
local.identifier.scopusID2-s2.0-33845909258
local.type.statusPublished Version

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