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OverviewThis book contains leading survey papers on the various aspects of abduction, both logical and numerical approaches. Abduction is central to all areas of applied reasoning, including artificial intelligence, philosophy of science, machine learning, data mining and decision theory, as well as logic itself. Full Product DetailsAuthor: Dov M. Gabbay , Philippe SmetsPublisher: Springer Imprint: Springer Edition: 2000 ed. Volume: 4 Dimensions: Width: 15.50cm , Height: 2.50cm , Length: 23.50cm Weight: 1.780kg ISBN: 9780792365655ISBN 10: 0792365658 Pages: 442 Publication Date: 30 September 2000 Audience: College/higher education , Professional and scholarly , Undergraduate , Postgraduate, Research & Scholarly Format: Hardback Publisher's Status: Active Availability: In Print ![]() This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us. Table of ContentsOn the Relation between Abduction and Inductive Learning; P.A. Flach, A.C. Kakas. Part I: Logical Approaches. AI Approaches to Abduction; G. Paul. Abduction in Labelled Deductive Systems; D.M. Gabbay. Logical Characterisations of Inductive Learning; P.A. Flach. Abduction in Machine Learning; F. Bergadano, V. Cutello, D. Gunetti. Part II: Numerical Approaches. An Overview of Ordinal and Numerical Approaches to Causal Diagnostic Problem Solving; D. Dubois, H. Prade. Abductive Inference with Probabilistic Networks; C. Borgelt, R. Kruse. Learning from Data: Possibilistic Graphical Models; J. Gebhardt. Independence in Uncertainty Theories and its Applications to Learning Belief Networks; L.M. de Campos, J.F. Huete, S. Moral. Index.ReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |