Abductive Reasoning and Learning (Hardcover)

Dov M. Gabbay

ISBN 10: 0792365658 / ISBN 13: 9780792365655

Editore: Kluwer Academic Publishers, Dordrecht, 2000

Riguardo questo articolo

Hardcover. 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. 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Codice articolo 9780792365655

Dati bibliografici

• Titolo: Abductive Reasoning and Learning (Hardcover)
• Editore: Kluwer Academic Publishers, Dordrecht
• Data di pubblicazione: 2000
• Lingua: Inglese
• ISBN 10: 0792365658
• ISBN 13: 9780792365655
• Rilegatura: Hardcover
• 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.