Key Features
* Make your computer smarter
* Handle qualitative and uncertain information
* Improve computational tractability to solve your problems easily
Description
Knowledge Representation, which lies at the core of Artificial Intelligence, is concerned with encoding knowledge on computers to enable systems to reason automatically.
The Handbook of Knowledge Representation is an up-to-date review of twenty-five key topics in knowledge representation, written by the leaders of each field.
This book is an essential resource for students, researchers and practitioners in all areas of Artificial Intelligence.
Readership
Graduate students and researchers in knowledge representation, graduate students and researchers in artificial intelligence, practitioners in artificial intelligence
Handbook of Knowledge Representation, 1st Edition
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
