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dc.contributor.authorBhargava, Nikhil
dc.contributor.authorWilliams, Brian C
dc.date.accessioned2020-06-02T17:44:59Z
dc.date.available2020-06-02T17:44:59Z
dc.date.issued2019-01
dc.date.submitted2018-11
dc.identifier.issn0004-3702
dc.identifier.urihttps://hdl.handle.net/1721.1/125621
dc.description.abstractIn temporal planning, many different temporal network formalisms are used to model real world situations. Each of these formalisms has different features which affect how easy it is to determine whether the underlying network of temporal constraints is consistent. While many of the simpler models have been well-studied from a computational complexity perspective, the algorithms developed for advanced models which combine features have very loose complexity bounds. In this paper, we provide tight completeness bounds for strong, weak, and dynamic controllability checking of temporal networks that have conditions, disjunctions, and temporal uncertainty. Our work exposes some of the subtle differences between these different structures and, remarkably, establishes a guarantee that all of these problems are computable in PSPACE.en_US
dc.description.sponsorshipToyota Research Institute under grant number LP-C000765-SRen_US
dc.language.isoen
dc.publisherElsevier BVen_US
dc.relation.isversionofhttp://dx.doi.org/10.1016/j.artint.2018.11.008en_US
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivs Licenseen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.sourcearXiven_US
dc.titleComplexity bounds for the controllability of temporal networks with conditions, disjunctions, and uncertaintyen_US
dc.typeArticleen_US
dc.identifier.citationBhargava, Nikhil, and Brian C. Williams. "Complexity bounds for the controllability of temporal networks with conditions, disjunctions, and uncertainty." Artificial Intelligence, 271 (June 2019): 1-17.en_US
dc.relation.journalArtificial Intelligenceen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2019-11-04T14:01:05Z
dspace.date.submission2019-11-04T14:01:10Z
mit.journal.volume271en_US
mit.licensePUBLISHER_CC
mit.metadata.statusComplete


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