Handbook of Knowledge Representation,
Edition 1Editors: Edited by Frank van Harmelen, Vladimir Lifschitz and Bruce Porter
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Description
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.
Key Features
- Make your computer smarter
- Handle qualitative and uncertain information
- Improve computational tractability to solve your problems easily
About the author
Edited by Frank van Harmelen, Vrije Universiteit Amsterdam, The Netherlands; Vladimir Lifschitz, University of Texas at Austin, USA and Bruce Porter, University of Texas at Austin, USA
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
Sowa: Knowledge Representation: Logical, Philosophical, and Computational Foundations. 2000. Pacific Grove: Brooks/Cole. ISBN: 9780534949655. $81.95. 608 pages. Bookscan: 2052
Gomez-Perez, Corcho, and Fernandez-Lopez: Ontological Engineering, 2005, Springer Publishers. ISBN: 9781852335519. $81.95. 415 pages. Bookscan: 681