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09181 Executive Summary – Sampling-based Optimization in the Presence of Uncertainty Branke, Jürgen Nelson, Barry L. Powell, Warren Buckler Santner, Thomas J. Optimal learning optimization in the presence of uncertainty simulation optimization sequential experimental design ranking and selection random search stochastic approximation approximate dynamic programming This Dagstuhl seminar brought together researchers from statistical ranking and selection; experimental design and response-surface modeling; stochastic programming; approximate dynamic programming; optimal learning; and the design and analysis of computer experiments with the goal of attaining a much better mutual understanding of the commonalities and differences of the various approaches to sampling-based optimization, and to take first steps toward an overarching theory, encompassing many of the topics above. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Jürgen Branke and Barry L. Nelson and Warren Buckler Powell and Thomas J. Santner 2009 Is Part Of Dagstuhl Seminar Proceedings, Volume 9181, Sampling-based Optimization in the Presence of Uncertainty (2009) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/DagSemProc.09181.2 urn:nbn:de:0030-drops-21161 https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.09181.2 eng https://creativecommons.org/licenses/by/4.0/legalcode