Hugendubel.info - Die B2B Online-Buchhandlung 

Merkliste
Die Merkliste ist leer.
Bitte warten - die Druckansicht der Seite wird vorbereitet.
Der Druckdialog öffnet sich, sobald die Seite vollständig geladen wurde.
Sollte die Druckvorschau unvollständig sein, bitte schliessen und "Erneut drucken" wählen.

Artificial Intelligence

A Modern Appoach. Global Edition
BuchKartoniert, Paperback
1152 Seiten
Englisch
PEVerschienen am18.05.20163rd ed.
For one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence. The long-anticipated revision of this best-selling text offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence.mehr

Produkt

KlappentextFor one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence. The long-anticipated revision of this best-selling text offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence.
ZusammenfassungFor one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence. The long-anticipated revision of this best-selling text offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. View chapters 3 and 4 from the Third Edition.
Details
ISBN/GTIN978-1-292-15396-4
ProduktartBuch
EinbandartKartoniert, Paperback
Verlag
Erscheinungsjahr2016
Erscheinungsdatum18.05.2016
Auflage3rd ed.
ReihePrentice Hall Series in Artificial Intelligence
Reihen-Nr.Intelligence
Seiten1152 Seiten
SpracheEnglisch
Gewicht1892 g
Illustrationenw. figs.
Artikel-Nr.15641069

Inhalt/Kritik

Inhaltsverzeichnis
I. Artificial Intelligence 1. Introduction2. Intelligent Agents II. Problem-solving 3. Solving Problems by Searching 4. Beyond Classical Search 5. Adversarial Search 6. Constraint Satisfaction Problems III. Knowledge, Reasoning, and Planning 7. Logical Agents 8. First-Order Logic 9. Inference in First-Order Logic 10. Classical Planning 11. Planning and Acting in the Real World 12 Knowledge Representation IV. Uncertain Knowledge and Reasoning13. Quantifying Uncertainty 14. Probabilistic Reasoning 15. Probabilistic Reasoning over Time 16. Making Simple Decisions 17. Making Complex Decisions V. Learning18. Learning from Examples 19. Knowledge in Learning 20. Learning Probabilistic Models 21. Reinforcement Learning VI. Communicating, Perceiving, and Acting22. Natural Language Processing 23. Natural Language for Communication 24. Perception 25. Robotics VII. Conclusions 26 Philosophical Foundations 27. AI: The Present and Future A. Mathematical Background B. Notes on Languages and Algorithms Bibliography Indexmehr