Abductive Reasoning and Learning: Volume 4: Abductive Reasoning and Learning (Handbook of Defeasible Reasoning and Uncertainty Management Systems)

Gabbay, Dov M.

ISBN 10: 9048155606 / ISBN 13: 9789048155606

Editore: Springer, 2010

Riguardo questo articolo

This 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. Editor(s): Gabbay, Dov M.; Smets, Philippe. Series: Handbook of Defeasible Reasoning & Uncertainty Management Systems. Num Pages: 442 pages, biography. BIC Classification: HPL; PBC; PBT; UYQ. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 23. Weight in Grams: 688. . 2010. Softcover reprint of the original 1st ed. 2000. Paperback. . . . . Books ship from the US and Ireland.

Codice articolo V9789048155606

Dati bibliografici

• Titolo: Abductive Reasoning and Learning: Volume 4: Abductive Reasoning and Learning (Handbook of Defeasible Reasoning and Uncertainty Management Systems)
• Editore: Springer
• Data di pubblicazione: 2010
• Lingua: Inglese
• ISBN 10: 9048155606
• ISBN 13: 9789048155606
• Rilegatura: Brossura
• Condizione: New

Descrizione articolo

Riassunto

This 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.

Contenuti

On 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.