Foundations of Inductive Logic Programming [electronic resource] / by Shan-Hwei Nienhuys-Cheng, Roland de Wolf.
Nienhuys-Cheng, Shan-Hwei. author.
Wolf, Roland de. author.
SpringerLink (Online service)
Computer science.
Software engineering.
Computer programming.
Mathematical logic.
Artificial intelligence.
QA76.758
005.1 23
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.
1997
Text
XVIII, 410 p.
http://dx.doi.org/10.1007/3-540-62927-0
eng
Springer eBooks
Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence, 0302-9743 ; 1228
Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence, 0302-9743 ; 1228