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Continuous State Dynamic Programming via Nonexpansive Approximation

Stachurski, John

Description

This paper studies fitted value iteration for continuous state numerical dynamic programming using nonexpansive function approximators. A number of approximation schemes are discussed. The main contribution is to provide error bounds for approximate optimal policies generated by the value iteration algorithm.

dc.contributor.authorStachurski, John
dc.date.accessioned2015-12-08T22:10:31Z
dc.identifier.issn0927-7099
dc.identifier.urihttp://hdl.handle.net/1885/29372
dc.description.abstractThis paper studies fitted value iteration for continuous state numerical dynamic programming using nonexpansive function approximators. A number of approximation schemes are discussed. The main contribution is to provide error bounds for approximate optimal policies generated by the value iteration algorithm.
dc.publisherSpringer
dc.sourceComputational Economics
dc.subjectKeywords: Nonexpansive approximation; Numerical dynamic programming
dc.titleContinuous State Dynamic Programming via Nonexpansive Approximation
dc.typeJournal article
local.description.notesImported from ARIES
local.identifier.citationvolume31
dc.date.issued2008
local.identifier.absfor140102 - Macroeconomic Theory
local.identifier.ariespublicationu9501697xPUB64
local.type.statusPublished Version
local.contributor.affiliationStachurski, John, College of Business and Economics, ANU
local.description.embargo2037-12-31
local.bibliographicCitation.issue2
local.bibliographicCitation.startpage141
local.bibliographicCitation.lastpage160
local.identifier.doi10.1007/s10614-007-9111-5
dc.date.updated2015-12-08T07:33:08Z
local.identifier.scopusID2-s2.0-40549131285
local.identifier.thomsonID000259102300003
CollectionsANU Research Publications

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