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Rating: 
Summary: this book not cover much
Review: I bought this book for my introduction course in AI. I feel that this book has lack of somethings which are very important, neural networks, and Ai and robotics to name a few. I found that the text is very hard to understand. Again he didn't use enough example to explain some of the topics. I am lost reading this book. The book is not well structured and turned me bored after 30 minutes reading it. The reason are, AI term definations are not included as other book do, few visual diagrams, objective is not well defined. Once again, he didn't include introduction/review of what we acpect to learn of each of every chapters. Reading it is like reading a "white bible". Only plain text and unprofessional layout. This book discorage me reading it. I think i should buy other book that have a wider coverage topics in AI and yet easy to understand, consistent with my AI course syllibus and yet easy for my eyes.
Rating: 
Summary: This is a good book for the beginners.
Review: The book presents many aspects like predicate logic, state space search,knowledge representation, natural language understanding, machine learning and specially programming in both LISP and PROLOG.I specially liked the chapters on learning, natural language understanding and the programming techniques.The book is unique for its presentation style, simplicity and illustrations. It must be on the desk of anyone interested to join the disciplines of AI.
Rating:
Summary: An excellent book for an intro to AI
Review: This book is actually a follow up to Luger and Stubblefield's older book "AI and the Design of Expert Systems". Being somewhat dated in both title and content, this book serves as its resurrection. Both books are excellent in providing a basic introduction to AI. They contain a number of problems and provide just enough infromation on each topic to give the reader the general idea and a sense of having learned something substantial (this is always the danger when writing a book that surveys a variety of interrelated fields). Another strength of the book is its ability to make connections between the different areas of AI. For example, when discussing knowledge representation, they make sure to draw connections with it and logic as well as natural language processing.
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Summary: LISP and Prolog all in one
Review: This book is almost a perfect solution for an introductory AI class, since it presents the chapters on both Prolog and LISP programming. The introduction to those languages is rather detailed, the Prolog chapter takes up about 75 pages while LISP introduction is almost 100 pages long. Without focusing on any particular subject in AI the book tends to be substantial and detailed.
Rating:
Summary: Fantastic Introduction to AI
Review: This book really stands out among the AI texts (I've read 4 others). First, the language is clear and simple enough for undergrads to grasp. Second, there are consistent examples that pervade the text to help the reader apply each method to an established problem. Third, the explanations of algorithms/structures are crafted and phrased to TEACH, not merely to summarize a bunch of material for reference purposes. Finally, the programming chapters allow the student to realize the material, and really think about the problems by implementing them and hashing out the details.
I cannot complain about any lack of depth - the length already exceeds 900 pages. To those that desire more, look into academic journals - this is an intro. Moreover, robotics, vision, neural nets, and other topics already have their own "forked" research fields, with textbooks of comparable length focusing on those topics alone!
Enjoy! This text is sure to get you started!
Rating: 
Summary: Good For Beginners in AI
Review: This is a very good book for anyone wanting to get an insight. Good for the first college course in AI too. It introduces the different areas of AI quite well, and develops logic before doing that. Prolog and LISP are also introduced.The only reason I wouldn't give this book 5 stars is because
1) The Prolog and LISP features aren't all that great. They could have done better than just explaining what they did. 2) There was very little or almost no depth in the material covered. I wanted to go on reading more about the advanced features, but that never happened. So, I had to go to the library and look for something there. But a great book for a college course. I wouldn't recommend this for a Grad course in CS...A grad student should be knowing beyond what this book covers.
Rating:
Summary: Don't miss it!
Review: This is the best general AI book I've seen this far. It introduces all the popular branches of AI clearly. If you are serious about AI, you should own this book...
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