- Hardcover: 784 pages
- Publisher: Addison Wesley; 6 edition (26 Feb 2008)
- Language English
- ISBN-10: 0321545893
- ISBN-13: 978-0321545893
- Product Dimensions: 23.2 x 19.3 x 3 cm
- Average Customer Review: 4.0 out of 5 stars See all reviews (1 customer review)
- Amazon Bestsellers Rank: 1,681,614 in Books (See Top 100 in Books)
- See Complete Table of Contents
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Product Description
Product Description
Artificial Intelligence: Structures and Strategies for Complex Problem Solving is ideal for a one- or two-semester undergraduate course on AI.
In this accessible, comprehensive text, George Luger captures the essence of artificial intelligence–solving the complex problems that arise wherever computer technology is applied. Ideal for an undergraduate course in AI, the Sixth Edition presents the fundamental concepts of the discipline first then goes into detail with the practical information necessary to implement the algorithms and strategies discussed. Readers learn how to use a number of different software tools and techniques to address the many challenges faced by today’s computer scientists.
In this accessible, comprehensive text, George Luger captures the essence of artificial intelligence–solving the complex problems that arise wherever computer technology is applied. Ideal for an undergraduate course in AI, the Sixth Edition presents the fundamental concepts of the discipline first then goes into detail with the practical information necessary to implement the algorithms and strategies discussed. Readers learn how to use a number of different software tools and techniques to address the many challenges faced by today’s computer scientists.
From the Back Cover
Artificial Intelligence
Structures and Strategies for Complex Problem Solving, Sixth Edition
by George F Luger
This accessible, comprehensive book captures the essence of artificial intelligence -- solving the complex problems that arise wherever computer technology is applied. With his signature enthusiasm, George Luger demonstrates numerous techniques and strategies for addressing the many challenges facing computer scientists today. Diverse topics on this exciting and ever-evolving field range from perception and adaptation using neural networks and genetic algorithms, intelligent agents with ontologies, automated reasoning, natural language analysis, and stochastic approaches to machine learning.
This book is ideal for a one - or two-semester university course on AI.
New to this edition:
- A new chapter on stochastic approaches to machine learning, including first-prder Bayesian networks, variants of hidden Markov models, inference with Markov random fields and loopy belief propagation.
- Presentation of parameter fitting with expectation maximization learning and structure learning using Markov chain Monte Carlo sampling. Use of Markov decision processes in reinforcement learning.
- Presentation of agent technology and the use of ontologies.
- Natural language processing with dynamic programming (the Earley parser) and other probabilistic parsing techniques including Viterbi.
- A new supplemental programming book is available: AI Algorithms in Prolog, Lisp, and Java™. Available online and in print, this book demonstrates these languages as tools for building many of the algorithms presented throughout Luger's AI book.
"There are many ideas in this area that students often find difficult; the clarity and precision of Luger's exposition is informed by sharp, incisive examples with straightforward graphical components."
-- Joseph Lewis, San Diego State University
"The book is a perfect complement to an AI course. It gives readers both an historical point of view and a practical guide to all the techniques. It is THE book I would recommend as an introduction to this field."
-- Pascal Rebreyend, Dalarna University
"The style of writing and comprehensive treatment of the subject matter makes this a valuable addition to the AI literature."
-- Malachy Eaton, University of Limerick
George Luger is currently a Professor of Computer Science, Linguistics, and Psychology at the University of New Mexico. He received his Ph.D. from the University of Pennsylvania and spent five years researching and teaching at the Department of Artificial Intelligence at the University of Edinburgh.
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Customer Reviews
Most Helpful Customer Reviews
4 of 4 people found the following review helpful
Format:Hardcover
In a way the title is too limited. As well as an excellent coverage of current and future directions in AI, it provides the grounding for an understanding of cognitive science and related topics.
I found the text comprehensive and lucid, though occasionally too fast-paced in explaining some concepts -- perhaps some of it is best read in conjunction with taught lectures, but other parts can be read purely for interest, wider reading or self-study.
Definitely comprehensive for an undergraduate study or broad postgraduate study of AI.
Most Helpful Customer Reviews on Amazon.com (beta)
Amazon.com:
9 reviews
19 of 22 people found the following review helpful
An excellent book for an intro to AI
17 Jan 2001
Format:Hardcover
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.
14 of 16 people found the following review helpful
Good For Beginners in AI
4 Dec 2002
Format:Hardcover
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.
13 of 15 people found the following review helpful
This is a good book for the beginners.
28 Mar 2000
Format:Hardcover
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.
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