This mathematically oriented introduction to the theory of logic programming presents a systematic exposition of the resolution method for propositional, first-order, and Horn- clause logics, together with an analysis of the semantic aspects of the method. It is through the inference rule of resolution that both proofs and computations can be manipulated on computers, and this book contains ele…
This book describes a complementary approach that views logic programs as grammars and shows how this new presentation of the foundations of logic programming, based on the notion of proof trees, can enrich the field.Within the field of logic programming there have been numerous attempts to transform grammars into logic programs. This book describes a complementary approach that views logic pro…
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 rece…
"This tutorial demystifies one of the most important yet poorly understood aspects of logic programming, the Warren Abstract Machine or WAM. The author's step-by-step construction of the WAM adds features in a gradual manner, clarifying the complex aspects of the design and providing the first detailed study of WAM since it was designed in 1983. Developed by David H.D. Warren, the WAM is an abs…
The job of the constraint programmer is to use mathematical constraints to model real world constraints and objects. In this book, Kim Marriott and Peter Stuckey provide the first comprehensive introduction to the discipline of constraint programming and, in particular, constraint logic programming. The book covers the necessary background material from artificial intelligence, logic programmin…