Buch, Englisch, 1034 Seiten, Format (B × H): 165 mm x 240 mm, Gewicht: 1960 g
Buch, Englisch, 1034 Seiten, Format (B × H): 165 mm x 240 mm, Gewicht: 1960 g
ISBN: 978-0-444-52211-5
Verlag: Elsevier Science & Technology
Handbook of Knowledge Representation describes the essential foundations of Knowledge Representation, which lies at the core of Artificial Intelligence (AI). The book provides an up-to-date review of twenty-five key topics in knowledge representation, written by the leaders of each field. It includes a tutorial background and cutting-edge developments, as well as applications of Knowledge Representation in a variety of AI systems.
This handbook is organized into three parts. Part I deals with general methods in Knowledge Representation and reasoning and covers such topics as classical logic in Knowledge Representation; satisfiability solvers; description logics; constraint programming; conceptual graphs; nonmonotonic reasoning; model-based problem solving; and Bayesian networks. Part II focuses on classes of knowledge and specialized representations, with chapters on temporal representation and reasoning; spatial and physical reasoning; reasoning about knowledge and belief; temporal action logics; and nonmonotonic causal logic. Part III discusses Knowledge Representation in applications such as question answering; the semantic web; automated planning; cognitive robotics; multi-agent systems; and knowledge engineering.
This book is an essential resource for graduate students, researchers, and practitioners in knowledge representation and AI.
Zielgruppe
Graduate students and researchers in knowledge representation, graduate students and researchers in artificial intelligence, practitioners in artificial intelligence
Autoren/Hrsg.
Weitere Infos & Material
Part I: General Methods in Knowledge Representation and Reasoning 1. Knowledge Representation and Classical Logic 2. Satisfiability Solvers 3. Description Logics 4. Constraint Programming 5. Conceptual Graphs 6. Nonmonotonic Reasoning 7. Answer Sets 8. Belief Revision 9. Qualitative Modeling 10. Model-Based Problem Solving 11. Bayesian Networks Part II: Classes of Knowledge and Specialized Representations 12. Temporal Representation and Reasoning 13. Spatial Reasoning 14. Physical Reasoning 15. Reasoning about Knowledge and Belief 16. Situation Calculus 17. Event Calculus 18. Temporal Action Logics 19. Nonmonotonic Causal Logic Part III: Knowledge Representation in Applications 20. Knowledge Representation and Question Answering 21. The Semantic Web: Webizing Knowledge Representation 22. Automated Planning 23. Cognitive Robotics 24. Multi-Agent Systems 25. Knowledge Engineering
