Show simple item record

On the benefits of argumentation-derived evidence in learning policies

dc.contributor.authorEmele, Chukwuemeka David
dc.contributor.authorNorman, Timothy J
dc.contributor.authorGuerin, Frank
dc.contributor.authorParsons, Simon
dc.date.accessioned2010-07-28T11:08:04Z
dc.date.available2010-07-28T11:08:04Z
dc.date.issued2011-12-01
dc.identifier140125941
dc.identifier23c61aec-ba4c-4e52-8453-1981b6f04aa0
dc.identifier84857492858
dc.identifier.citationEmele , C D , Norman , T J , Guerin , F & Parsons , S 2011 , On the benefits of argumentation-derived evidence in learning policies . in Argumentation in Multi-Agent Systems - 7th International Workshop, ArgMAS 2010, Revised, Selected and Invited Papers . Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) , vol. 6614 LNAI , pp. 86-104 , Seventh International Workshop on Argumentation in Multi-Agent Systems , Toronto , Ontario , Canada , 10/05/10 . https://doi.org/10.1007/978-3-642-21940-5_6en
dc.identifier.citationworkshopen
dc.identifier.isbn9783642219399
dc.identifier.issn0302-9743
dc.identifier.otherORCID: /0000-0003-1918-6311/work/64219156
dc.identifier.urihttp://hdl.handle.net/2164/720
dc.format.extent19
dc.format.extent369756
dc.language.isoeng
dc.relation.ispartofArgumentation in Multi-Agent Systems - 7th International Workshop, ArgMAS 2010, Revised, Selected and Invited Papersen
dc.relation.ispartofseriesLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)en
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subject.lccQA75en
dc.titleOn the benefits of argumentation-derived evidence in learning policiesen
dc.typeConference itemen
dc.contributor.institutionUniversity of Aberdeen.Computing Scienceen
dc.identifier.doi10.1007/978-3-642-21940-5_6
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=84857492858&partnerID=8YFLogxKen


Files in this item

Thumbnail
Name:
argmas2010_submission_11.pdf
Size:
361.0Kb
Format:
PDF
View/Open

This item appears in the following Collection(s)

Show simple item record