1.

Record Nr.

UNINA9910968154603321

Titolo

Handbook of knowledge representation / / edited by Bruce Porter, Vladimir Lifschitz and Frank van Harmelen

Pubbl/distr/stampa

Amsterdam, : Elsevier, 2008

ISBN

9786611144944

9781281144942

1281144940

9780080557021

0080557023

Edizione

[1st ed.]

Descrizione fisica

1 online resource (1035 p.)

Collana

Foundations of artificial intelligence

Altri autori (Persone)

PorterBruce <1956->

LifschitzVladimir

Van HarmelenFrank

Disciplina

006.332

Soggetti

Knowledge representation (Information theory)

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references and indexes.

Nota di contenuto

Front cover; Handbook of Knowledge Representation; Copyright page; Dedication; Preface; Editors; Contributors; 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 Methods2.3 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 Tractability4.5 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 ConclusionAcknowledgements; 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 Modeling9.1 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

Sommario/riassunto

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 yo