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Using machine learning for decreasing state uncertainty in planning

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Krivic, Senka
dc.contributor.author Cashmore, Michael
dc.contributor.author Magazzeni, Daniele
dc.contributor.author Szedmak, Sandor
dc.contributor.author Piater, Justus
dc.date.accessioned 2021-02-26T07:13:18Z
dc.date.available 2021-02-26T07:13:18Z
dc.date.issued 2020-11-11
dc.identifier.citation Krivic , S , Cashmore , M , Magazzeni , D , Szedmak , S & Piater , J 2020 , ' Using machine learning for decreasing state uncertainty in planning ' , Journal of Artificial Intelligence Research , vol. 69 , pp. 765-806 . https://doi.org/10.1613/JAIR.1.11567 en
dc.identifier.issn 1076-9757
dc.identifier.other PURE UUID: 7ba8448f-cfd9-4976-96b8-9d41ab98dbe2
dc.identifier.other PURE ITEMURL: https://research.aalto.fi/en/publications/7ba8448f-cfd9-4976-96b8-9d41ab98dbe2
dc.identifier.other PURE LINK: http://www.scopus.com/inward/record.url?scp=85097217016&partnerID=8YFLogxK
dc.identifier.other PURE FILEURL: https://research.aalto.fi/files/55981888/Krivic_Using_machinge_learning.11567_Article_PDF_24931_1_10_20201111.pdf
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/102786
dc.description.abstract We present a novel approach for decreasing state uncertainty in planning prior to solving the planning problem. This is done by making predictions about the state based on currently known information, using machine learning techniques. For domains where uncertainty is high, we define an active learning process for identifying which information, once sensed, will best improve the accuracy of predictions. We demonstrate that an agent is able to solve problems with uncertainties in the state with less planning effort compared to standard planning techniques. Moreover, agents can solve problems for which they could not find valid plans without using predictions. Experimental results also demonstrate that using our active learning process for identifying information to be sensed leads to gathering information that improves the prediction process. en
dc.format.extent 42
dc.format.extent 765-806
dc.format.mimetype application/pdf
dc.language.iso en en
dc.publisher Morgan Kaufmann Publishers, Inc.
dc.relation.ispartofseries Journal of Artificial Intelligence Research en
dc.relation.ispartofseries Volume 69 en
dc.rights openAccess en
dc.title Using machine learning for decreasing state uncertainty in planning en
dc.type A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä fi
dc.description.version Peer reviewed en
dc.contributor.department King’s College London
dc.contributor.department University of Strathclyde
dc.contributor.department Professorship Rousu Juho
dc.contributor.department University of Innsbruck
dc.contributor.department Department of Computer Science en
dc.identifier.urn URN:NBN:fi:aalto-202102262075
dc.identifier.doi 10.1613/JAIR.1.11567
dc.type.version publishedVersion

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