Inductive Logic Programming: From Machine Learning to Software Engineering (Logic Programming) - Hardcover

Bergadano, Francesco; Gunetti, Daniele

Hardcover

ISBN 10: 0262023938 ISBN 13: 9780262023931

Publisher: Mit Pr, 1995

Synopsis

Although Inductive Logic Programming (ILP) is generally thought of as a research area at the intersection of machine learning and computational logic, Bergadano and Gunetti propose that most of the research in ILP has in fact come from machine learning, particularly in the evolution of inductive reasoning from pattern recognition, through initial approaches to symbolic machine learning, to recent techniques for learning relational concepts. In this book they provide an extended, up-to-date survey of ILP, emphasizing methods and systems suitable for software engineering applications, including inductive program development, testing, and maintenance. Inductive Logic Programming includes a definition of the basic ILP problem and its variations (incremental, with queries, for multiple predicates and predicate invention capabilities), a description of bottom-up operators and techniques (such as least general generalization, inverse resolution, and inverse implication), an analysis of top-down methods (mainly MIS and FOIL-like systems), and a survey of methods and languages for specifying inductive bias. Logic Programming series

About this title

About the Author

Francesco Bergadano is Professor in the Department of Computer Science at the University of Turin.

Review

"This is a very fine essay on naturalistic epistemology. Kornblith's work will be a distinctive contribution at the interface of philosophy and cognitive science." Alvin I. Goldman, University of Arizona

Edition details

• Publisher: Mit Pr
• Publication date: 1995
• ISBN 10: 0262023938
• ISBN 13: 9780262023931
• Binding: Hardcover
• Language: English
• Number of pages: 256