Harmelen / Lifschitz / Porter Handbook of Knowledge Representation

1. Auflage 2008
ISBN: 978-0-08-055702-1
Verlag: Elsevier Science & Techn.
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 1034 Seiten, Web PDF

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.* Make your computer smarter
* Handle qualitative and uncertain information
* Improve computational tractability to solve your problems easily

Autoren/Hrsg.

Harmelen, Frank Van

Lifschitz, Vladimir

Porter, Bruce

Inhaltsverzeichnis

1;Front cover;1
2;Handbook of Knowledge Representation;4
3;Copyright page;5
4;Dedication;6
5;Preface;8
6;Editors;12
7;Contributors;14
8;Contents;16
9;Part I: General Methods in Knowledge Representation and Reasoning;30
9.1;Chapter 1. Knowledge Representation and Classical Logic;32
9.1.1;1.1 Knowledge Representation and Classical Logic;32
9.1.2;1.2 Syntax, Semantics and Natural Deduction;33
9.1.3;1.3 Automated Theorem Proving;47
9.1.4;1.4 Applications of Automated Theorem Provers;87
9.1.5;1.5 Suitability of Logic for Knowledge Representation;96
9.1.6;Acknowledgements;103
9.1.7;Bibliography;103
9.2;Chapter 2. Satisfiability Solvers;118
9.2.1;2.1 Definitions and Notation;120
9.2.2;2.2 SAT Solver Technology-Complete Methods;121
9.2.3;2.3 SAT Solver Technology-Incomplete Methods;136
9.2.4;2.4 Runtime Variance and Problem Structure;141
9.2.5;2.5 Beyond SAT: Quantified Boolean Formulas and Model Counting;146
9.2.6;Bibliography;151
9.3;Chapter 3. Description Logics;164
9.3.1;3.1 Introduction;164
9.3.2;3.2 A Basic DL and its Extensions;168
9.3.3;3.3 Relationships with other Formalisms;173
9.3.4;3.4 Tableau Based Reasoning Techniques;175
9.3.5;3.5 Complexity;180
9.3.6;3.6 Other Reasoning Techniques;184
9.3.7;3.7 DLs in Ontology Language Applications;195
9.3.8;3.8 Further Reading;197
9.3.9;Bibliography;198
9.4;Chapter 4. Constraint Programming;210
9.4.1;4.1 Introduction;210
9.4.2;4.2 Constraint Propagation;211
9.4.3;4.3 Search;213
9.4.4;4.4 Tractability;218
9.4.5;4.5 Modeling;220
9.4.6;4.6 Soft Constraints and Optimization;222
9.4.7;4.7 Constraint Logic Programming;226
9.4.8;4.8 Beyond Finite Domains;228
9.4.9;4.9 Distributed Constraint Programming;230
9.4.10;4.10 Application Areas;231
9.4.11;4.11 Conclusions;232
9.4.12;Bibliography;232
9.5;Chapter 5. Conceptual Graphs;242
9.5.1;5.1 From Existential Graphs to Conceptual Graphs;242
9.5.2;5.2 Common Logic;246
9.5.3;5.3 Reasoning with Graphs;252
9.5.4;5.4 Propositions, Situations, and Metalanguage;259
9.5.5;5.5 Research Extensions;262
9.5.6;Bibliography;264
9.6;Chapter 6. Nonmonotonic Reasoning;268
9.6.1;6.1 Introduction;268
9.6.2;6.2 Default Logic;271
9.6.3;6.3 Autoepistemic Logic;281
9.6.4;6.4 Circumscription;289
9.6.5;6.5 Nonmonotonic Inference Relations;296
9.6.6;6.6 Further Issues and Conclusion;301
9.6.7;Acknowledgements;306
9.6.8;Bibliography;306
9.7;Chapter 7. Answer Sets;314
9.7.1;7.1 Introduction;314
9.7.2;7.2 Syntax and Semantics of Answer Set Prolog;315
9.7.3;7.3 Properties of Logic Programs;321
9.7.4;7.4 A Simple Knowledge Base;329
9.7.5;7.5 Reasoning in Dynamic Domains;331
9.7.6;7.6 Extensions of Answer Set Prolog;336
9.7.7;7.7 Conclusion;338
9.7.8;Acknowledgements;339
9.7.9;Bibliography;339
9.8;Chapter 8. Belief Revision;346
9.8.1;8.1 Introduction;346
9.8.2;8.2 Preliminaries;347
9.8.3;8.3 The AGM Paradigm;347
9.8.4;8.4 Belief Base Change;358
9.8.5;8.5 Multiple Belief Change;364
9.8.6;8.6 Iterated Revision;369
9.8.7;8.7 Non-Prioritized Revision;375
9.8.8;8.8 Belief Update;378
9.8.9;8.9 Conclusion;381
9.8.10;Acknowledgements;382
9.8.11;Bibliography;382
9.9;Chapter 9. Qualitative Modeling;390
9.9.1;9.1 Introduction;390
9.9.2;9.2 Qualitative Mathematics;394
9.9.3;9.3 Ontology;400
9.9.4;9.4 Causality;403
9.9.5;9.5 Compositional Modeling;405
9.9.6;9.6 Qualitative States and Qualitative Simulation;408
9.9.7;9.7 Qualitative Spatial Reasoning;410
9.9.8;9.8 Qualitative Modeling Applications;412
9.9.9;9.9 Frontiers and Resources;416
9.9.10;Bibliography;416
9.10;Chapter 10. Model-based Problem Solving;424
9.10.1;10.1 Introduction;424
9.10.2;10.2 Tasks;427
9.10.3;10.3 Requirements on Modeling;432
9.10.4;10.4 Diagnosis;436
9.10.5;10.5 Test and Measurement Proposal, Diagnosability Analysis;467
9.10.6;10.6 Remedy Proposal;475
9.10.7;10.7 Other Tasks;483
9.10.8;10.8 State and Challenges;487
9.10.9;Acknowledgements;489
9.10.10;Bibliography;489
9.11;Chapter 11. Bayesian Networks;496
9.11.1;11.1 Introduction;496
9.11.2;11.2 Syntax and Semantics of Bayesian Networks;497
9.11.3;11.3 Exact Inference;502
9.11.4;11.4 Approximate Inference;514
9.11.5;11.5 Constructing Bayesian Networks;518
9.11.6;11.6 Causality and Intervention;526
9.11.7;Acknowledgements;527
9.11.8;Bibliography;528
10;Part II: Classes of Knowledge and Specialized Representations;540
10.1;Chapter 12. Temporal Representation and Reasoning;542
10.1.1;12.1 Temporal Structures;543
10.1.2;12.2 Temporal Language;549
10.1.3;12.3 Temporal Reasoning;557
10.1.4;12.4 Applications;559
10.1.5;12.5 Concluding Remarks;564
10.1.6;Acknowledgements;564
10.1.7;Bibliography;564
10.2;Chapter 13. Qualitative Spatial Representation and Reasoning;580
10.2.1;13.1 Introduction;580
10.2.2;13.2 Aspects of Qualitative Spatial Representation;583
10.2.3;13.3 Spatial Reasoning;601
10.2.4;13.4 Reasoning about Spatial Change;610
10.2.5;13.5 Cognitive Validity;611
10.2.6;13.6 Final Remarks;612
10.2.7;Acknowledgements;613
10.2.8;Bibliography;613
10.3;Chapter 14. Physical Reasoning;626
10.3.1;14.1 Architectures;629
10.3.2;14.2 Domain Theories;631
10.3.3;14.3 Abstraction and Multiple Models;640
10.3.4;14.4 Historical and Bibliographical;643
10.3.5;Bibliography;647
10.4;Chapter 15. Reasoning about Knowledge and Belief;650
10.4.1;15.1 Introduction;650
10.4.2;15.2 The Possible Worlds Model;651
10.4.3;15.3 Properties of Knowledge;655
10.4.4;15.4 The Knowledge of Groups;657
10.4.5;15.5 Runs and Systems;662
10.4.6;15.6 Adding Time;664
10.4.7;15.7 Knowledge-based Behaviors;666
10.4.8;15.8 Beyond Square One;672
10.4.9;15.9 How to Reason about Knowledge and Belief;673
10.4.10;Bibliography;674
10.4.11;Further reading;676
10.5;Chapter 16. Situation Calculus;678
10.5.1;16.1 Axiomatizations;679
10.5.2;16.2 The Frame, the Ramification and the Qualification Problems;681
10.5.3;16.3 Reiter's Foundational Axioms and Basic Action Theories;690
10.5.4;16.4 Applications;694
10.5.5;16.5 Concluding Remarks;696
10.5.6;Acknowledgements;696
10.5.7;Bibliography;696
10.6;Chapter 17. Event Calculus;700
10.6.1;17.1 Introduction;700
10.6.2;17.2 Versions of the Event Calculus;701
10.6.3;17.3 Relationship to other Formalisms;713
10.6.4;17.4 Default Reasoning;713
10.6.5;17.5 Event Calculus Knowledge Representation;716
10.6.6;17.6 Action Language E;726
10.6.7;17.7 Automated Event Calculus Reasoning;728
10.6.8;17.8 Applications of the Event Calculus;729
10.6.9;Bibliography;730
10.7;Chapter 18. Temporal Action Logics;738
10.7.1;18.1 Introduction;738
10.7.2;18.2 Basic Concepts;742
10.7.3;18.3 TAL Narratives;745
10.7.4;18.4 The Relation Between the TAL Languages L(ND) and L(FL) ;753
10.7.5;18.5 The TAL Surface Language L(ND);754
10.7.6;18.6 The TAL Base Language L(FL);757
10.7.7;18.7 Circumscription and TAL;759
10.7.8;18.8 Representing Ramifications in TAL;764
10.7.9;18.9 Representing Qualifications in TAL;766
10.7.10;18.10 Action Expressivity in TAL;771
10.7.11;18.11 Concurrent Actions in TAL;773
10.7.12;18.12 An Application of TAL: TALplanner;776
10.7.13;18.13 Summary;781
10.7.14;Acknowledgements;781
10.7.15;Bibliography;782
10.8;Chapter 19. Nonmonotonic Causal Logic;788
10.8.1;19.1 Fundamentals;791
10.8.2;19.2 Strong Equivalence;794
10.8.3;19.3 Completion;795
10.8.4;19.4 Expressiveness;797
10.8.5;19.5 High-Level Action Language C+;799
10.8.6;19.6 Relationship to Default Logic;800
10.8.7;19.7 Causal Theories in Higher-Order Classical Logic;801
10.8.8;19.8 A Logic of Universal Causation;802
10.8.9;Acknowledgement;803
10.8.10;Bibliography;803
11;Part III: Knowledge Representation in Applications;806
11.1;Chapter 20. Knowledge Representation and Question Answering;808
11.1.1;20.1 Introduction;808
11.1.2;20.2 From English to Logical Theories;812
11.1.3;20.3 The COGEX Logic Prover of the LCC QA System;819
11.1.4;20.4 Extracting Relevant Facts from Logical Theories and its Use in the DD QA System about Dynamic Domains and Trips;821
11.1.5;20.5 From Natural Language to Relevant Facts in the ASU QA System;832
11.1.6;20.6 Nutcracker-System for Recognizing Textual Entailment;835
11.1.7;20.7 Mueller's Story Understanding System;839
11.1.8;20.8 Conclusion;842
11.1.9;Acknowledgements;844
11.1.10;Bibliography;844
11.2;Chapter 21. The Semantic Web: Webizing Knowledge Representation;850
11.2.1;21.1 Introduction;850
11.2.2;21.2 The Semantic Web Today;852
11.2.3;21.3 Semantic Web KR Language Design;855
11.2.4;21.4 OWL-Defining a Semantic Web KR Language ;860
11.2.5;21.5 Semantic Web KR Challenges;865
11.2.6;21.6 Beyond OWL;865
11.2.7;21.7 Conclusion;866
11.2.8;Acknowledgements;866
11.2.9;Bibliography;867
11.3;Chapter 22. Automated Planning;870
11.3.1;22.1 Introduction;870
11.3.2;22.2 The General Framework;872
11.3.3;22.3 Strong Planning under Full Observability;874
11.3.4;22.4 Strong Cyclic Planning under Full Observability;876
11.3.5;22.5 Planning for Temporally Extended Goals under Full Observability;879
11.3.6;22.6 Conformant Planning;886
11.3.7;22.7 Strong Planning under Partial Observability;888
11.3.8;22.8 A Technological Overview;889
11.3.9;22.9 Conclusions;892
11.3.10;Bibliography;893
11.4;Chapter 23. Cognitive Robotics;898
11.4.1;23.1 Introduction;898
11.4.2;23.2 Knowledge Representation for Cognitive Robots;899
11.4.3;23.3 Reasoning for Cognitive Robots;902
11.4.4;23.4 High-Level Control for Cognitive Robots;905
11.4.5;23.5 Conclusion;910
11.4.6;Bibliography;911
11.5;Chapter 24. Multi-Agent Systems;916
11.5.1;24.1 Introduction;916
11.5.2;24.2 Representing Rational Cognitive States;917
11.5.3;24.3 Representing the Strategic Structure of a System;938
11.5.4;24.4 Conclusions;949
11.5.5;Bibliography;949
11.6;Chapter 25. Knowledge Engineering;958
11.6.1;25.1 Introduction;958
11.6.2;25.2 Baseline;958
11.6.3;25.3 Tasks and Problem-Solving Methods;959
11.6.4;25.4 Ontologies;965
11.6.5;25.5 Knowledge Elicitation Techniques;970
11.6.6;Bibliography;972
12;Author Index;976
13;Subject Index;1016