Answer Set Programming (2019) [pdf] (www.cs.utexas.edu)

A new draft book on Answer Set Programming (ASP), authored by Vladimir Lifschitz from the University of Texas at Austin, was recently shared with the AI and computational logic community. This comprehensive resource, based on an undergraduate class, explores the methodology and mathematics behind ASP, particularly using the clingo system—one of the most efficient and prominent ASP solvers available. The book covers fundamental concepts in declarative programming, logic programming constructs, problem-solving techniques, and dynamic system representations. The significance of this development lies in the increasing relevance of ASP in various scientific and technological applications, as it offers a powerful approach to automated reasoning. The book's structure, which includes exercises and detailed discussions of both theoretical underpinnings and practical implementations, is designed to enhance understanding and application of ASP concepts. By addressing how ASP can represent actions and generate plans, the draft highlights its potential for solving complex computational problems, thus contributing to advancements in artificial intelligence and knowledge representation.