Knowledge representation and reasoning is the foundation of artificial intelligence, declarative programming, and the design of knowledge-intensive software systems capable of performing intelligent tasks. Using logical and probabilistic formalisms based on answer set programming (ASP) and action languages, this book shows how knowledge-intensive systems can be given knowledge about the world and how it can be used to solve non-trivial computational problems. The authors maintain a balance between mathematical analysis and practical design of intelligent agents. All the concepts, such as answering queries, planning, diagnostics, and probabilistic reasoning, are illustrated by programs of ASP. The text can be used for AI-related undergraduate and graduate classes and by researchers who would like to learn more about ASP and knowledge representation.
|Publisher:||Cambridge University Press|
|Edition description:||New Edition|
|Product dimensions:||6.10(w) x 9.10(h) x 1.00(d)|
Table of Contents
1. Logic-based approach to agent design; 2. Answer set Prolog (ASP); 3. Roots of ASP; 4. Creating a knowledge base; 5. Representing defaults; 6. The answer set programming paradigm; 7. Algorithms for computing answer sets; 8. Modeling dynamic domains; 9. Planning agents; 10. Diagnostic agents; 11. Probabilistic reasoning; 12. The Prolog programming language.