Foundations of Inductive Logic Programming (Lecture Notes in Computer Science, 1228)

Nienhuys-Cheng, Shan-Hwei; Wolf, Ronald De

ISBN 10: 3540629270 / ISBN 13: 9783540629276

Editore: Springer, 1997

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Dati bibliografici

• Titolo: Foundations of Inductive Logic Programming (Lecture Notes in Computer Science, 1228)
• Editore: Springer
• Data di pubblicazione: 1997
• Lingua: Inglese
• ISBN 10: 3540629270
• ISBN 13: 9783540629276
• Rilegatura: Brossura
• Condizione: New

Descrizione articolo

Riassunto

Inductive Logic Programming is a young and rapidly growing field combining machine learning and logic programming. This self-contained tutorial is the first theoretical introduction to ILP; it provides the reader with a rigorous and sufficiently broad basis for future research in the area.
In the first part, a thorough treatment of first-order logic, resolution-based theorem proving, and logic programming is given. The second part introduces the main concepts of ILP and systematically develops the most important results on model inference, inverse resolution, unfolding, refinement operators, least generalizations, and ways to deal with background knowledge. Furthermore, the authors give an overview of PAC learning results in ILP and of some of the most relevant implemented systems.

Contenuti

Propositional logic.- First-order logic.- Normal forms and Herbrand models.- Resolution.- Subsumption theorem and refutation completeness.- Linear and input resolution.- SLD-resolution.- SLDNF-resolution.- What is inductive logic programming?.- The framework for model inference.- Inverse resolution.- Unfolding.- The lattice and cover structure of atoms.- The subsumption order.- The implication order.- Background knowledge.- Refinement operators.- PAC learning.- Further topics.