Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/73573
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dc.titleLightning does not strike twice: Robust MDPs with coupled uncertainty
dc.contributor.authorMannor, S.
dc.contributor.authorMebel, O.
dc.contributor.authorXu, H.
dc.date.accessioned2014-06-19T05:36:46Z
dc.date.available2014-06-19T05:36:46Z
dc.date.issued2012
dc.identifier.citationMannor, S.,Mebel, O.,Xu, H. (2012). Lightning does not strike twice: Robust MDPs with coupled uncertainty. Proceedings of the 29th International Conference on Machine Learning, ICML 2012 1 : 385-392. ScholarBank@NUS Repository.
dc.identifier.isbn9781450312851
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/73573
dc.description.abstractWe consider Markov decision processes under parameter uncertainty. Previous studies all restrict to the case that uncertainties among different states are uncoupled, which leads to conservative solutions. In contrast, we introduce an intuitive concept, termed "Lightning Does not Strike Twice," to model coupled uncertain parameters. Specifically, we require that the system can deviate from its nominal parameters only a bounded number of times. We give probabilistic guarantees indicating that this model represents real life situations and devise tractable algorithms for computing optimal control policies. Copyright 2012 by the author(s)/owner(s).
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentMECHANICAL ENGINEERING
dc.description.sourcetitleProceedings of the 29th International Conference on Machine Learning, ICML 2012
dc.description.volume1
dc.description.page385-392
dc.identifier.isiutNOT_IN_WOS
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