Declarative Logic Programming: Theory, Systems, and Applications

Abstract

Logic Programming (LP) is at the nexus of knowledge representation, AI, mathematical logic, databases, and programming languages. It allows programming to be more declarative, by specifying “what” to do instead of “how” to do it. This field is fascinating and intellectually stimulating due to the fundamental interplay among theory, systems, and applications brought about by logic. Several books cover the basics of LP but they focus mostly on the Prolog language. There is generally a lack of accessible collections of articles covering the key aspects of LP, such as the well-founded vs. stable semantics for negation, constraints, object-oriented LP, updates, probabilistic LP, and implementation methods, including top-down vs. bottom-up evaluation and tabling. For systems, the situation is even less satisfactory, lacking expositions of LP inference machinery that supports tabling and other state-of-the-art implementation techniques. There is also a dearth of articles about systems that support truly declarative languages, especially those that tie into first-order logic, mathematical programming, and constraint programming. Also rare are surveys of challenging application areas of LP, such as bioinformatics, natural language processing, verification, and planning, as well as analysis of LP applications based on language abstractions and implementations methods. The goal of this book is to help fill in the void in the literature with state-of-the-art surveys on key aspects of LP. Much attention was paid to making these surveys accessible to researchers, practitioners, and graduate students alike.