Handbook of Knowledge Representation 1st Edition by Frank van Harmelen, Vladimir Lifschitz, Bruce Porter 0444522115 9780444522115
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ISBN 10: 0444522115
ISBN 13: 9780444522115
Author: Frank van Harmelen, Vladimir Lifschitz, Bruce Porter
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.
* Make your computer smarter
* Handle qualitative and uncertain information
* Improve computational tractability to solve your problems easily
Handbook of Knowledge Representation 1st Table of contents:
Part I: General Methods in Knowledge Representation and Reasoning
Chapter 1. Knowledge Representation and Classical Logic
1.1 Knowledge Representation and Classical Logic
1.2 Syntax, Semantics and Natural Deduction
1.3 Automated Theorem Proving
1.4 Applications of Automated Theorem Provers
1.5 Suitability of Logic for Knowledge Representation
Acknowledgements
Bibliography
Chapter 2. Satisfiability Solvers
2.1 Definitions and Notation
2.2 SAT Solver Technology-Complete Methods
2.3 SAT Solver Technology-Incomplete Methods
2.4 Runtime Variance and Problem Structure
2.5 Beyond SAT: Quantified Boolean Formulas and Model Counting
Bibliography
Chapter 3. Description Logics
3.1 Introduction
3.2 A Basic DL and its Extensions
3.3 Relationships with other Formalisms
3.4 Tableau Based Reasoning Techniques
3.5 Complexity
3.6 Other Reasoning Techniques
3.7 DLs in Ontology Language Applications
3.8 Further Reading
Bibliography
Chapter 4. Constraint Programming
4.1 Introduction
4.2 Constraint Propagation
4.3 Search
4.4 Tractability
4.5 Modeling
4.6 Soft Constraints and Optimization
4.7 Constraint Logic Programming
4.8 Beyond Finite Domains
4.9 Distributed Constraint Programming
4.10 Application Areas
4.11 Conclusions
Bibliography
Chapter 5. Conceptual Graphs
5.1 From Existential Graphs to Conceptual Graphs
5.2 Common Logic
5.3 Reasoning with Graphs
5.4 Propositions, Situations, and Metalanguage
5.5 Research Extensions
Bibliography
Chapter 6. Nonmonotonic Reasoning
6.1 Introduction
6.2 Default Logic
6.3 Autoepistemic Logic
6.4 Circumscription
6.5 Nonmonotonic Inference Relations
6.6 Further Issues and Conclusion
Acknowledgements
Bibliography
Chapter 7. Answer Sets
7.1 Introduction
7.2 Syntax and Semantics of Answer Set Prolog
7.3 Properties of Logic Programs
7.4 A Simple Knowledge Base
7.5 Reasoning in Dynamic Domains
7.6 Extensions of Answer Set Prolog
7.7 Conclusion
Acknowledgements
Bibliography
Chapter 8. Belief Revision
8.1 Introduction
8.2 Preliminaries
8.3 The AGM Paradigm
8.4 Belief Base Change
8.5 Multiple Belief Change
8.6 Iterated Revision
8.7 Non-Prioritized Revision
8.8 Belief Update
8.9 Conclusion
Acknowledgements
Bibliography
Chapter 9. Qualitative Modeling
9.1 Introduction
9.2 Qualitative Mathematics
9.3 Ontology
9.4 Causality
9.5 Compositional Modeling
9.6 Qualitative States and Qualitative Simulation
9.7 Qualitative Spatial Reasoning
9.8 Qualitative Modeling Applications
9.9 Frontiers and Resources
Bibliography
Chapter 10. Model-based Problem Solving
10.1 Introduction
10.2 Tasks
10.3 Requirements on Modeling
10.4 Diagnosis
10.5 Test and Measurement Proposal, Diagnosability Analysis
10.6 Remedy Proposal
10.7 Other Tasks
10.8 State and Challenges
Acknowledgements
Bibliography
Chapter 11. Bayesian Networks
11.1 Introduction
11.2 Syntax and Semantics of Bayesian Networks
11.3 Exact Inference
11.4 Approximate Inference
11.5 Constructing Bayesian Networks
11.6 Causality and Intervention
Acknowledgements
Bibliography
Part II: Classes of Knowledge and Specialized Representations
Chapter 12. Temporal Representation and Reasoning
12.1 Temporal Structures
12.2 Temporal Language
12.3 Temporal Reasoning
12.4 Applications
12.5 Concluding Remarks
Acknowledgements
Bibliography
Chapter 13. Qualitative Spatial Representation and Reasoning
13.1 Introduction
13.2 Aspects of Qualitative Spatial Representation
13.3 Spatial Reasoning
13.4 Reasoning about Spatial Change
13.5 Cognitive Validity
13.6 Final Remarks
Acknowledgements
Bibliography
Chapter 14. Physical Reasoning
14.1 Architectures
14.2 Domain Theories
14.3 Abstraction and Multiple Models
14.4 Historical and Bibliographical
Bibliography
Chapter 15. Reasoning about Knowledge and Belief
15.1 Introduction
15.2 The Possible Worlds Model
15.3 Properties of Knowledge
15.4 The Knowledge of Groups
15.5 Runs and Systems
15.6 Adding Time
15.7 Knowledge-based Behaviors
15.8 Beyond Square One
15.9 How to Reason about Knowledge and Belief
Bibliography
Further reading
Chapter 16. Situation Calculus
16.1 Axiomatizations
16.2 The Frame, the Ramification and the Qualification Problems
16.3 Reiter’s Foundational Axioms and Basic Action Theories
16.4 Applications
16.5 Concluding Remarks
Acknowledgements
Bibliography
Chapter 17. Event Calculus
17.1 Introduction
17.2 Versions of the Event Calculus
17.3 Relationship to other Formalisms
17.4 Default Reasoning
17.5 Event Calculus Knowledge Representation
17.6 Action Language E
17.7 Automated Event Calculus Reasoning
17.8 Applications of the Event Calculus
Bibliography
Chapter 18. Temporal Action Logics
18.1 Introduction
18.2 Basic Concepts
18.3 TAL Narratives
18.4 The Relation Between the TAL Languages L(ND) and L(FL)
18.5 The TAL Surface Language L(ND)
18.6 The TAL Base Language L(FL)
18.7 Circumscription and TAL
18.8 Representing Ramifications in TAL
18.9 Representing Qualifications in TAL
18.10 Action Expressivity in TAL
18.11 Concurrent Actions in TAL
18.12 An Application of TAL: TALplanner
18.13 Summary
Acknowledgements
Bibliography
Chapter 19. Nonmonotonic Causal Logic
19.1 Fundamentals
19.2 Strong Equivalence
19.3 Completion
19.4 Expressiveness
19.5 High-Level Action Language C+
19.6 Relationship to Default Logic
19.7 Causal Theories in Higher-Order Classical Logic
19.8 A Logic of Universal Causation
Acknowledgement
Bibliography
Part III: Knowledge Representation in Applications
Chapter 20. Knowledge Representation and Question Answering
20.1 Introduction
20.2 From English to Logical Theories
20.3 The COGEX Logic Prover of the LCC QA System
20.4 Extracting Relevant Facts from Logical Theories and its Use in the DD QA System about Dynamic D
20.5 From Natural Language to Relevant Facts in the ASU QA System
20.6 Nutcracker-System for Recognizing Textual Entailment
20.7 Mueller’s Story Understanding System
20.8 Conclusion
Acknowledgements
Bibliography
Chapter 21. The Semantic Web: Webizing Knowledge Representation
21.1 Introduction
21.2 The Semantic Web Today
21.3 Semantic Web KR Language Design
21.4 OWL-Defining a Semantic Web KR Language
21.5 Semantic Web KR Challenges
21.6 Beyond OWL
21.7 Conclusion
Acknowledgements
Bibliography
Chapter 22. Automated Planning
22.1 Introduction
22.2 The General Framework
22.3 Strong Planning under Full Observability
22.4 Strong Cyclic Planning under Full Observability
22.5 Planning for Temporally Extended Goals under Full Observability
22.6 Conformant Planning
22.7 Strong Planning under Partial Observability
22.8 A Technological Overview
22.9 Conclusions
Bibliography
Chapter 23. Cognitive Robotics
23.1 Introduction
23.2 Knowledge Representation for Cognitive Robots
23.3 Reasoning for Cognitive Robots
23.4 High-Level Control for Cognitive Robots
23.5 Conclusion
Bibliography
Chapter 24. Multi-Agent Systems
24.1 Introduction
24.2 Representing Rational Cognitive States
24.3 Representing the Strategic Structure of a System
24.4 Conclusions
Bibliography
Chapter 25. Knowledge Engineering
25.1 Introduction
25.2 Baseline
25.3 Tasks and Problem-Solving Methods
25.4 Ontologies
25.5 Knowledge Elicitation Techniques
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