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Title: Artificial Intelligence: A Modern Approach (2nd Edition) by Stuart J. Russell, Peter Norvig ISBN: 0-13-790395-2 Publisher: Prentice Hall Pub. Date: 20 December, 2002 Format: Hardcover Volumes: 1 List Price(USD): $89.00 |
Average Customer Rating: 4.02 (42 reviews)
Rating: 5
Summary: Fantistic Introduction to an Interesting Field
Comment: AI: A Modern Approach is a great introduction to a good range of topics in the field of AI. Going into this book, I knew nothing of AI. The first few chapters cover intelligent agents, searching, and various search algorithms such as the basics like Depth-First and Breadth-First, and then the book introduces some more intelligent algorithms like A*, SMA*, Iterative Deepening, and a few more. Other topics included in the book are planning, logic (if you're new to logic, I might recommend some supplimentary material; it's very important to understand everything if you're interested in AI). I've read several introductory books on AI, and I would definately rate this one as the best!
Rating: 5
Summary: the best AI textbook available now
Comment: Comments from my students
Comments on AI: A Modern Approach
Having used this book, I have found it to be an excellent overview of modern AI techniques. In fact, I knew nothing about many of the subjects in this book before this course, and this book has helped intrigue my interest sufficiently into the field.
This book uses an intelligent agent as the unifying theme throughout. Namely, the problem of AI is to describe and build agents that receive percepts from the environment and perform actions, and each such agent is implemented by a function that maps percepts to actions. It covers different ways to represent these functions, such as production systems, reactive agents, logical planners and decision-theoretic systems. It explains the role of learning as extending the reach of the designer into unknown environments, and shows how it constrains agent design. All in all, the book is quite readable and well organized.
In addition, the references to important works in the field were extremely useful, especially since many of them are now available online. What¡¯s more, these exercises are complete and thorough. They cover the entire breadth of the chapter, and each are detailed enough to challenge the students as more than a trivial problem.
While each topic is treated carefully and explanations are clear, unfortunately the book would run to many volumes if each topic was covered completely. Since this is not the aim of the book, this is not a drawback. AI:AMA is, after all, an introductory text to AI used in many undergraduate AI courses. Every one who is learning AI should have this book on their shelf.
Student ID: 0020309059
Comments on ¡°Artificial Intelligence-A modern Approach¡±
I think this book is the leading textbook in Artificial Intelligence I have ever read. The Artificial Intelligence is a big area, this book give me a whole view of it.
Besides all those good idea in this textbook, I think there is flaw in AIMI 2nd.
First of all the whole book doesn¡¯t have a detailed example that can lead reader the way to build AI application from scratch although there are many little examples and figures in the book. I think AI is a practical subject.
Second, Agent is hot and useful in AI now. I think there should be more pages on Agent and the application of Agent.
Comments on ¡°Artificial Intelligence-A modern Approach¡±
I think this book is fairly valuable both for the beginners and for the specialists. This book has the following three characteristics compared with the books on AI that I read before:
A new perspective of building intelligent agents: The book is organized around intelligent agents: what the ideas of agent are; how they make decisions and get information; how they learn knowledge. From this perspective a wide array of materials on AI is well organized and presented to the readers clearly and readably. Finished this book, I found myself have attained an overview of Artificial Intelligence.
This text book is organized using the latest principles of good textbook design. It includes historical notes at the end of every chapter, exercises, margin notes, a bibliography, and a competent index. The historical notes are much helpful to me, from which I could get much information on the corresponding domains and I could read more that I am interested.
The text book contains many valuable and comprehensive examples to illustrate the ideas it presents. The exercise is also good. They are both helpful to me to grasp the knowledge of AI.
Besides those small examples which are responsible for illustrate the basic ideas and concepts, one or two ¡®big¡¯ examples which illustrate the process of building practical artificial intelligent systems must be helpful to us.
I am a graduate student who major in Computer Science. I use the book ¡°Artificial Intelligence¡± as my textbook in the course of AI. After one semester¡¯s study, I find this book is a good one. As we all know, AI is a big field, and it is very difficult to write a good book of AI because that book must be a big one. But the style, the concept and the practicability of this book are excellent.
Firstly, when I read the book, I was deeply absorbing by its style. It describes the key concepts of a problem and its solution first, then give examples, and finally give a theoretical explanation, with rigorous theoretical analysis where appropriate. The point of the theory is always to get the concepts across and explain how they are used in actual, fielded systems. During the course of my reading, I had a clear mind. I could find the right reason why this problem could be promoted, what¡¯s the mathematic model of it, and how it could be solved in several methods.
Secondly, I enjoy the concept of the book. I think the writer must have a good sense of humor. I clearly remembered I fell into a big laughed when I read the example that ¡°if you left your car outside all the night, you might find your spare tyro missing next morning.¡± What a funny story it is!
Finally, the practicability of the book is good. Because of its comprehensive coverage and large number of detailed algorithms, it is useful as a primary reference volume for me.
Just as Prof. Tom Dietterich has said: ¡°I recommend it to anyone who wants to have an introductory overview of the state of AI. And I recommend it to experts in the field, who will enjoy its unified description of the field.¡±
Rating: 1
Summary: Survey type of book, shallow but good for reference
Comment: In ONE world: 'self-filler'
This book is not really an introduction to Computational Intelligence, for an introductory type of book read David E. Goldberg's Genetic Algorithms Book, it is exceptional in terms of readability, concepts presented and depths it gradually delves into. That is the father of all genetic algorithm/EC/AI books, in my humble opinion.
I know most of the stuff in Engelbrecht's book now, not because I've read it from his book, but because I've learnt it from other sources, do yourself a favor, read more descriptive aind insightful material about AI and CI. the chapters on NN and SOM, GA, EC are very shallow, he just summarizes ideas you can get from reading free sources like, AI webpages, presents a bunch of formulas, and to understand what they mean, you have to refer to the glossary and appendices. Furthermore he is inconsistent in his symbols, the terms represented by his symbols change through-out the book, sometimes even in consecutive chapters.
Stuff he never addresses: Taboo Search, Simulated Annealing aren't even mentioned in the book. Travelling salesman problems, snake in the box, hybrid systems, neuro fuzzy system, adaptive genetic fuzzy systems are all never mentioned. There are no examples of the uses of the material he covers, kind of takes the flavor away from what you're reading. It is bland, fonts are awful, and pictures are drawn with Microcrap's paintbrush. This book will never give you an insight into CI paradigms, if you already know that stuff and want a quick revision, or want a reference for the formulas, get this book, or else it's just a shelf-filler.
If you want to learn about AI/CI ideas go to www.mathworld.com (it's matlab's webpage), you'll learn a lot more in an easier way.
Also search the web, it contains almost all the information you need about latest CI research, go to www.citeseer.com and read research papers.
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Title: Machine Learning by Tom M. Mitchell ISBN: 0070428077 Publisher: McGraw-Hill Science/Engineering/Math Pub. Date: 01 March, 1997 List Price(USD): $166.00 |
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Title: Introduction to Algorithms, Second Edition by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein ISBN: 0262032937 Publisher: MIT Press Pub. Date: 01 September, 2001 List Price(USD): $79.95 |
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Title: AI Application Programming by M. Tim Jones ISBN: 1584502789 Publisher: Charles River Media Pub. Date: 27 March, 2003 List Price(USD): $54.95 |
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Title: ANSI Common LISP by Paul Graham ISBN: 0133708756 Publisher: Prentice Hall Pub. Date: 02 November, 1995 List Price(USD): $47.00 |
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Title: Artificial Intelligence (3rd Edition) by Winston ISBN: 0201533774 Publisher: Addison-Wesley Pub Co Pub. Date: 15 January, 1992 List Price(USD): $101.00 |
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