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dc.contributor.authorAphale, M. S.
dc.contributor.authorNorman, T. J.
dc.contributor.authorŞensoy, Murat
dc.date.accessioned2016-02-15T07:33:15Z
dc.date.available2016-02-15T07:33:15Z
dc.date.issued2014
dc.identifier.isbn978-1-4503-2738-1
dc.identifier.urihttp://hdl.handle.net/10679/2153
dc.identifier.urihttp://dl.acm.org/citation.cfm?id=2616026
dc.descriptionDue to copyright restrictions, the access to the full text of this article is only available via subscription.
dc.description.abstractWe address the problem of developing effective automated reasoning support for the detection and resolution of conflicts between plans and policies (or norms). How automated reasoning mechanisms can effectively support human decision makers in this process is little understood. In this research, we have conducted experiments with human subjects to assess how effective these reasoning mechanisms are. We found that providing guidance to users regarding what problems to prioritise and highlighting related conflicts led to higher quality outcomes, and problems were successfully solved more rapidly.
dc.description.sponsorshipRCUK Digital Economy Programme
dc.language.isoengen_US
dc.publisherSpringer Science+Business Media
dc.relation.ispartofAAMAS '14 Proceedings of the 2014 international conference on Autonomous agents and multi-agent systems
dc.rightsrestrictedAccess
dc.titleGoal directed policy conflict detection and prioritisation: an empirical evaluationen_US
dc.typeConference paperen_US
dc.peerreviewedyes
dc.publicationstatuspublisheden_US
dc.contributor.departmentÖzyeğin University
dc.contributor.authorID41438
dc.contributor.ozuauthorŞensoy, Murat
dc.identifier.startpage1489
dc.identifier.endpage1490
dc.subject.keywordsPolicies
dc.subject.keywordsNorms
dc.subject.keywordsConflict resolution
dc.identifier.scopusSCOPUS:2-s2.0-84911397243
dc.contributor.authorMale1


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