Artificial Intelligence - A Modern Approach(3rd Edition)

Artificial Intelligence - A Modern Approach(3rd Edition)

Stuart J. Russell / Peter Norvig
星期二, 十二月 1, 2009


Artificial Intelligence: A Modern Approach, 3e offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Number one in its field, this textbook is ideal for one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence.
Dr. Peter Norvig, contributing Artificial Intelligence author and Professor Sebastian Thrun, a Pearson author are offering a free online course at Stanford University on artificial intelligence.
According to an article in The New York Times , the course on artificial intelligence is “one of three being offered experimentally by the Stanford computer science department to extend technology knowledge and skills beyond this elite campus to the entire world.” One of the other two courses, an introduction to database software, is being taught by Pearson author Dr. Jennifer Widom.
Artificial Intelligence: A Modern Approach, 3e is available to purchase as an eText for your Kindle™, NOOK™, and the iPhone®/iPad®.
To learn more about the course on artificial intelligence, visit To read the full New York Times article, click here.


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
A Mathematical background
B Notes on Languages and Algorithms