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10302 Summary – Learning paradigms in dynamic environments Hammer, Barbara Hitzler, Pascal Maass, Wolfgang Toussaint, Marc Summary The seminar centered around problems which arise in the context of machine learning in dynamic environments. Particular emphasis was put on a couple of specific questions in this context: how to represent and abstract knowledge appropriately to shape the problem of learning in a partially unknown and complex environment and how to combine statistical inference and abstract symbolic representations; how to infer from few data and how to deal with non i.i.d. data, model revision and life-long learning; how to come up with efficient strategies to control realistic environments for which exploration is costly, the dimensionality is high and data are sparse; how to deal with very large settings; and how to apply these models in challenging application areas such as robotics, computer vision, or the web. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Barbara Hammer and Pascal Hitzler and Wolfgang Maass and Marc Toussaint 2010 Is Part Of Dagstuhl Seminar Proceedings, Volume 10302, Learning paradigms in dynamic environments (2010) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/DagSemProc.10302.2 urn:nbn:de:0030-drops-28027 https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.10302.2 eng https://creativecommons.org/licenses/by/4.0/legalcode