(P/B) ARTIFICIAL INTELLIGENCE

Παρουσίαση

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. (From the publisher)

Περιεχόμενα

I. Artificial Intelligence
1. Introduction
2. 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 Reasoning
13. Quantifying Uncertainty
14. Probabilistic Reasoning
15. Probabilistic Reasoning over Time
16. Making Simple Decisions
17. Making Complex Decisions
V. Learning
18. Learning from Examples
19. Knowledge in Learning
20. Learning Probabilistic Models
21. Reinforcement Learning
VI. Communicating, Perceiving, and Acting
22. Natural Language Processing
23. Natural Language for Communication
24. Perception
25. Robotics
VII. Conclusions
26 Philosophical Foundations
27. AI: The Present and Future
Appendices
A. Mathematical Background
A.1 Complexity Analysis and O() Notation
A.2 Vectors, Matrices, and Linear Algebra
A.3 Probability Distributions
B. Notes on Languages and Algorithms
B.1 Defining Languages with Backus - Naur Form (BNF)
B.2 Describing Algorithms with Pseudocode
B.3 Online Help
Bibliography
Index