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Viser: Artificial Intelligence: a Modern Approach, Global Edition
Artificial Intelligence: a Modern Approach, Global Edition
Stuart Russell og Peter Norvig
(2016)
Pearson Education, Limited
765,00 kr.
688,50 kr.
Denne bog er blevet erstattet af en nyere udgave.
Denne bog er blevet erstattet af Artificial Intelligence: a Modern Approach, Global Edition, 4. udgave
Detaljer om varen
- 3. Udgave
- Paperback: 1152 sider
- Udgiver: Pearson Education, Limited (Maj 2016)
- Forfattere: Stuart Russell og Peter Norvig
- ISBN: 9781292153964
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.
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
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
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