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Artificial Intelligence: A New Synthesis
 
 
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Artificial Intelligence: A New Synthesis [Hardcover]

Nils J. Nilsson (Author)
2.8 out of 5 stars  See all reviews (15 customer reviews)

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Book Description

April 15, 1998 1558604677 978-1558604674 1

Intelligent agents are employed as the central characters in this new introductory text. Beginning with elementary reactive agents, Nilsson gradually increases their cognitive horsepower to illustrate the most important and lasting ideas in AI. Neural networks, genetic programming, computer vision, heuristic search, knowledge representation and reasoning, Bayes networks, planning, and language understanding are each revealed through the growing capabilities of these agents. The book provides a refreshing and motivating new synthesis of the field by one of AI's master expositors and leading researchers. Artificial Intelligence: A New Synthesis takes the reader on a complete tour of this intriguing new world of AI.

* An evolutionary approach provides a unifying theme
* Thorough coverage of important AI ideas, old and new
* Frequent use of examples and illustrative diagrams
* Extensive coverage of machine learning methods throughout the text
* Citations to over 500 references
* Comprehensive index


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Editorial Reviews

From the Back Cover

Intelligent agents are employed as the central characters in this new introductory text. Beginning with elementary reactive agents, Nilsson gradually increases their cognitive horsepower to illustrate the most important and lasting ideas in AI. Neural networks, genetic programming, computer vision, heuristic search, knowledge representation and reasoning, Bayes networks, planning, and language understanding are each revealed through the growing capabilities of these agents. The book provides a refreshing and motivating new synthesis of the field by one of AI's master expositors and leading researchers. Artificial Intelligence: A New Synthesis takes the reader on a complete tour of this intriguing new world of AI.


Features


  • An evolutionary approach provides a unifying theme
  • Thorough coverage of important AI ideas, old and new
  • Frequent use of examples and illustrative diagrams
  • Extensive coverage of machine learning methods throughout the text
  • Citations to over 500 references
  • Comprehensive index

About the Author

Nils J. Nilsson's long and rich research career has contributed much to AI. He has written many books, including the classic Principles of Artificial Intelligence. Dr. Nilsson is Kumagai Professor of Engineering, Emeritus, at Stanford University. He has served on the editorial boards of Artificial Intelligence and Machine Learning and as an Area Editor for the Journal of the Association for Computing Machinery. Former Chairman of the Department of Computer Science at Stanford, and former Director of the SRI Artificial Intelligence Center, he is also a past president and Fellow of the American Association for Artificial Intelligence.


Product Details

  • Hardcover: 513 pages
  • Publisher: Morgan Kaufmann Publishers, Inc.; 1 edition (April 15, 1998)
  • Language: English
  • ISBN-10: 1558604677
  • ISBN-13: 978-1558604674
  • Product Dimensions: 9.6 x 7.7 x 1.4 inches
  • Shipping Weight: 2.4 pounds (View shipping rates and policies)
  • Average Customer Review: 2.8 out of 5 stars  See all reviews (15 customer reviews)
  • Amazon Best Sellers Rank: #495,415 in Books (See Top 100 in Books)

More About the Author

Nils J. Nilsson, Kumagai Professor of Engineering (Emeritus) in the Department of Computer Science at Stanford University, received his PhD degree in Electrical Engineering from Stanford in 1958. He spent twenty-three years at the Artificial Intelligence Center of SRI International working on statistical and neural-network approaches to pattern recognition, co-inventing the A* heuristic search algorithm and the STRIPS automatic planning system, directing work on the integrated mobile robot, SHAKEY, and collaborating in the development of the PROSPECTOR expert system. He has published five textbooks on artificial intelligence.

Professor Nilsson returned to Stanford in 1985 as the Chairman of the Department of Computer Science, a position he held until August 1990. Besides teaching courses on artificial intelligence and on machine learning, he has conducted research on flexible robots that are able to react to dynamic worlds, plan courses of action, and learn from experience. Professor Nilsson served on the editorial boards of the journal Artificial Intelligence and of the Journal of Artificial Intelligence Research. He was an Area Editor for the Journal of the Association for Computing Machinery. He is a past-president and Fellow of the American Association for Artificial Intelligence and is also a Fellow of the American Association for the Advancement of Science. He was a co-founder of Morgan Kaufmann Publishers, Inc.

Professor Nilsson is a foreign member of the Royal Swedish Academy of Engineering Sciences. He is a recipient of the IEEE "Neural-Network Pioneer" award, the IJCAI "Research Excellence" award, and the AAAI "Distinguished Service" award.

 

Customer Reviews

15 Reviews
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Average Customer Review
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7 of 7 people found the following review helpful:
2.0 out of 5 stars Not bad but mis-titled, June 29, 2000
This review is from: Artificial Intelligence: A New Synthesis (Hardcover)
Where is the synthesis? I didn't see it. The material is too dense for beginners, too scattered for the non-beginner.
There are several places where the author states something absolutely intriguing and moves on in the next sentence. For example, after much discussion of handling probability, he states that Bayesian networks are probably the way to go. And that's all that was said, "Wait, wait" I wanted to shout. "Tell me more about why you believe that!" But alas that's all there is.

Also, this book is probably too detailed for non-programmers, not detailed enough for programmers.

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11 of 13 people found the following review helpful:
4.0 out of 5 stars An interesting read for the advanced students, January 6, 2001
By 
G P (Seattle, WA United States) - See all my reviews
This review is from: Artificial Intelligence: A New Synthesis (Hardcover)
According to my former AI prof, Nilsson suffers from "Physics envy." Given that AI is a fairly new, fairly splintered facet of Computer Science research, there is a relative absence of quantitative analyses of the subject to rival such other fields as chemistry, biology, or physics. As such, Nilsson resorts to quantifying most every piece of data or concept in the book. In some cases, his formulas can more lucidly be explained in words or simple algebra, rather than polynomic summations and calculus.

Nevertheless, for the non-beginning student of computer science that has an interest in the subject, this book covers the gamut of AI subjects. Topics include neural networks, genetic programming, multi-agent programming, fuzzy logic, and machine vision. While no topic is covered in-depth, the broad scope of the book allows one entering the field to decide what areas, if any, are of paramount interest.

I recommend this book for a 2nd or 3rd year CS undergraduate with a background in calculus and with a serious interest in artificial intelligence.

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5 of 5 people found the following review helpful:
1.0 out of 5 stars confusing, poorly written, January 28, 2000
By A Customer
This review is from: Artificial Intelligence: A New Synthesis (Hardcover)
This is one of the worst textbooks I have ever had to use. It is confusing, poorly written, and incomplete. Russell and Norvig contains virtually all this material (plus much more) but present it in a much clearer way.
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Inside This Book (learn more)
First Sentence:
"Artificial Intelligence (AI), broadly (and somewhat circularly) defined, is concerned with intelligent behavior in artifacts." Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
following positive instances, goal wff, effective branching factor, initial state description, goal node, sigmoid unit, resolution refutation, evidence nodes, monotone condition, tip nodes, goal clause, depth bound, iconic model, start node, search graph, disagreement set, node expansion, proof tree, iterative deepening, move blank, interpretation satisfies, most general unifier, consistent labeling, empty clause, heuristic function
Key Phrases - Capitalized Phrases (CAPs): (learn more)
The Most Fit Individual, Alan Turing, Alpine Club, Converting Arbitrary, Courtesy of Matt Ginsberg, Garry Kasparov, International Conference, Models of Other Agents, Review of Probability Theory, Width of Gaussian
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