Foundations of inductive logic programming. Lecture notes in computer science ; Vol. 1228 : Lecture notes in artificial intelligence

Nienhuys-Cheng, Shan-Hwei and Ronald de Wolf:

ISBN 10: 3540629270 / ISBN 13: 9783540629276

Editore: Berlin ; Heidelberg ; Singapore ; Tokyo ; New York ; Barcelona ; Budapest ; Hong Kong ; London ; Milan ; Paris ; Santa Clara : Springer, 1997

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404 Seiten; Das hier angebotene Buch stammt aus einer teilaufgelösten wissenschaftlichen Bibliothek und trägt die entsprechenden Kennzeichnungen (Rückenschild, Instituts-Stempel.); leichte altersbedingte Anbräunung des Papiers; der Buchzustand ist ansonsten ordentlich und dem Alter entsprechend gut. Einbandkanten sind leicht bestoßen. In ENGLISCHER Sprache. Sprache: Englisch Gewicht in Gramm: 570. Codice articolo 1797420

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Titolo: Foundations of inductive logic programming. ...

Casa editrice: Berlin ; Heidelberg ; Singapore ; Tokyo ; New York ; Barcelona ; Budapest ; Hong Kong ; London ; Milan ; Paris ; Santa Clara : Springer

Data di pubblicazione: 1997

Legatura: Broschiert

Condizione: Gut

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.