Artificial Intelligence: A Modern Approach (2nd Edition) Review

Average Reviews:

(More customer reviews)I didn't think that the first edition of this book was as bad as some of the reviewers said, but the second edition is definitely a vast improvement. It's not just some obligatory 2nd edition that some authors release to say that they are staying actively published. The first edition was somewhat confusing in its explanations and the exercises were really blurry on what was being asked. All of that has now been resolved.
The book is a comprehensive and insightful introduction to artificial intelligence with an academic tone. It provides a unified view of the field organized around the rational decision making paradigm, which focuses on the selection of the "best" solution to a problem. The book's overall theme is that the purpose of AI is to solve problems via intelligent agents, and then goes about specifying the features such an agent or agents should have. Pseudocode is provided for all of the major AI algorithms. Being about the broadest book in terms of coverage of AI, you should therefore not expect it to be the deepest in coverage. However, each topic is covered to the extent that the reader should understand its essence. Sections one through six are absolutely wonderful, and comprise the "meat" of AI. Section seven is rather weak since it tries to cover both robotics and text processing in their own individual chapters, and entire books have a hard time covering this material. Section eight is different from the others, since it talks about the philosophy and future of AI.
Another plus for this book is that there is a great deal of extra material that deals with standard AI curriculum. For example, the chapters on logic not only include the typical introduction to propositional and first order logic together with the usual inference procedures, they also give many useful hints how to use first order logic to actually represent aspects of the real world such as measures, time, actions, mental objects, etc. These chapters also contain much information about how to implement efficient logical reasoners.
Finally, this second edition has an excellent website that can be found by going through the publisher's webpage for the book. This website contains four sample chapters, pseudocode, and actual code in Java, Python, and LISP.
I notice that Amazon shows the table of contents from the first edition, so I am showing what the actual table of contents is for the second edition for the purpose of completeness. Note that the book has been significantly reorganized.
I. ARTIFICIAL INTELLIGENCE.
1. Introduction.
2. Intelligent Agents.
II. PROBLEM-SOLVING.
3. Solving Problems by Searching.
4. Informed Search and Exploration.
5. Constraint Satisfaction Problems.
6. Adversarial Search.
III. KNOWLEDGE AND REASONING.
7. Logical Agents.
8. First-Order Logic.
9. Inference in First-Order Logic.
10. Knowledge Representation.
IV. PLANNING.
11. Planning.
12. Planning and Acting in the Real World.
V. UNCERTAIN KNOWLEDGE AND REASONING.
13. Uncertainty.
14. Probabilistic Reasoning Systems.
15. Probabilistic Reasoning Over Time.
16. Making Simple Decisions.
17. Making Complex Decisions.
VI. LEARNING.
18. Learning from Observations.
19. Knowledge in Learning.
20. Statistical Learning Methods.
21. Reinforcement Learning.
VII. COMMUNICATING, PERCEIVING, AND ACTING.
22. Agents that Communicate.
23. Text Processing in the Large.
24. Perception.
25. Robotics.
VIII. CONCLUSIONS.
26. Philosophical Foundations.
27. AI: Present and Future.

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