
Overview
Part of the book series: Lecture Notes in Computer Science (LNCS, volume 1228)
Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)
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About this book
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.
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Table of contents (19 chapters)
Bibliographic Information
Book Title: Foundations of Inductive Logic Programming
Authors: Shan-Hwei Nienhuys-Cheng, Roland Wolf
Series Title: Lecture Notes in Computer Science
DOI: https://doi.org/10.1007/3-540-62927-0
Publisher: Springer Berlin, Heidelberg
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eBook Packages: Springer Book Archive
Copyright Information: Springer-Verlag Berlin Heidelberg 1997
Softcover ISBN: 978-3-540-62927-6Published: 18 April 1997
eBook ISBN: 978-3-540-69049-8Published: 01 July 2005
Series ISSN: 0302-9743
Series E-ISSN: 1611-3349
Edition Number: 1
Number of Pages: XVIII, 410
Topics: Software Engineering/Programming and Operating Systems, Artificial Intelligence, Mathematical Logic and Formal Languages, Programming Techniques