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AuthorSchach, Sonjadc.contributor.author
AuthorGottwald, Sebastiandc.contributor.author
AuthorBraun, Daniel A.dc.contributor.author
Date of accession2019-01-21T10:08:22Zdc.date.accessioned
Available in OPARU since2019-01-21T10:08:22Zdc.date.available
Date of first publication2018-12-14dc.date.issued
AbstractExpected utility models are often used as a normative baseline for human performance in motor tasks. However, this baseline ignores computational costs that are incurred when searching for the optimal strategy. In contrast, bounded rational decision-theory provides a normative baseline that takes computational effort into account, as it describes optimal behavior of an agent with limited information-processing capacity to change a prior motor strategy (before information-processing) into a posterior strategy (after information-processing). Here, we devised a pointing task where subjects had restricted reaction and movement time. In particular, we manipulated the permissible reaction time as a proxy for the amount of computation allowed for planning the movements. Moreover, we tested three different distributions over the target locations to induce different prior strategies that would influence the amount of required information-processing. We found that movement endpoint precision generally decreases with limited planning time and that non-uniform prior probabilities allow for more precise movements toward high-probability targets. Considering these constraints in a bounded rational decision model, we found that subjects were generally close to bounded optimal. We conclude that bounded rational decision theory may be a promising normative framework to analyze human sensorimotor performance.dc.description.abstract
Languageen_USdc.language.iso
PublisherUniversität Ulmdc.publisher
LicenseCC BY 4.0 Internationaldc.rights
Link to license texthttp://creativecommons.org/licenses/by/4.0/dc.rights.uri
KeywordBounded rationalitydc.subject
KeywordMotor controldc.subject
KeywordMovement planningdc.subject
KeywordOptimality modeldc.subject
KeywordReaction timedc.subject
KeywordInformation-processing resourcesdc.subject
KeywordComputational costdc.subject
Dewey Decimal GroupDDC 004 / Data processing & computer sciencedc.subject.ddc
LCSHHuman information processingdc.subject.lcsh
TitleQuantifying motor task performance by bounded rational decision theorydc.title
Resource typeWissenschaftlicher Artikeldc.type
VersionpublishedVersiondc.description.version
DOIhttp://dx.doi.org/10.18725/OPARU-11360dc.identifier.doi
URNhttp://nbn-resolving.de/urn:nbn:de:bsz:289-oparu-11417-8dc.identifier.urn
GNDEingeschränkte Rationalitätdc.subject.gnd
GNDBewegungssteuerungdc.subject.gnd
GNDOptimalitätstheoriedc.subject.gnd
GNDReaktionszeitdc.subject.gnd
FacultyFakultät für Ingenieurwissenschaften, Informatik und Psychologieuulm.affiliationGeneral
InstitutionInstitut für Neuroinformatikuulm.affiliationSpecific
Peer reviewjauulm.peerReview
DCMI TypeTextuulm.typeDCMI
CategoryPublikationenuulm.category
Is Supplemented Byhttps://www.frontiersin.org/articles/10.3389/fnins.2018.00932/full#supplementary-materialuulm.relation.isSupplementedBy
DOI of original publication10.3389/fnins.2018.00932dc.relation1.doi
Source - Title of sourceFrontiers in Neurosciencesource.title
Source - Place of publicationFrontiers Mediasource.publisher
Source - Volume2018source.volume
Source - Issue12source.issue
Source - Year2018source.year
Source - Article number932source.articleNumber
Source - ISSN1662-4548source.identifier.issn
EU projectBRISC / Bounded Rationality in Sensorimotor Coordination / EC / H2020 / 678082uulm.projectEU
FundingEmmy Noether Projekt Computational and Biological Principles of Sensorimotor Learning / DFG [BR 4164/1-1, 192398156]uulm.funding


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CC BY 4.0 International
Except where otherwise noted, this item's license is described as CC BY 4.0 International