Artificial Intelligence

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. View chapters 3 and 4 from the Third Edition.

**** 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.

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Autorentext
Peter Norvig ist Director for Search Quality bei Google, Inc. Er war vorher an der University of Southern California und der University of California in Berkeley tätig.

Inhalt

• 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
• Index