Practical solution techniques for first-order MDPs

dc.contributor.authorSanner, Scott
dc.contributor.authorBoutilier, Craig
dc.date.accessioned2015-12-10T22:23:52Z
dc.date.issued2009
dc.date.updated2016-02-24T11:43:55Z
dc.description.abstractMany traditional solution approaches to relationally specified decision-theoretic planning problems (e.g., those stated in the probabilistic planning domain description language, or PPDDL) ground the specification with respect to a specific instantiation
dc.identifier.issn0004-3702
dc.identifier.urihttp://hdl.handle.net/1885/53008
dc.publisherElsevier
dc.sourceArtificial Intelligence
dc.subjectKeywords: Formal logic; Linearization; Specifications; Approximate linear programming; Decision-theoretic; First orders; First-order logic; International planning competitions; Markov decision process; MDPs; Planning problems; Practical solutions; Probabilistic pla First-order logic; MDPs; Planning
dc.titlePractical solution techniques for first-order MDPs
dc.typeJournal article
local.bibliographicCitation.lastpage788
local.bibliographicCitation.startpage748
local.contributor.affiliationSanner, Scott, College of Engineering and Computer Science, ANU
local.contributor.affiliationBoutilier, Craig, University of Toronto
local.contributor.authoruidSanner, Scott, u1817461
local.description.embargo2037-12-31
local.description.notesImported from ARIES
local.identifier.absfor080101 - Adaptive Agents and Intelligent Robotics
local.identifier.ariespublicationu8803936xPUB261
local.identifier.citationvolume173
local.identifier.doi10.1016/j.artint.2008.11.003
local.identifier.scopusID2-s2.0-60549103706
local.type.statusPublished Version

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