Download Ebook Artificial Intelligence (3rd Edition)
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Artificial Intelligence (3rd Edition)
Download Ebook Artificial Intelligence (3rd Edition)
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Amazon.com Review
This book is one of the oldest and most popular introductions to artificial intelligence. An accomplished artificial intelligence (AI) scientist, Winston heads MIT's Artificial Intelligence Laboratory, and his hands-on AI research experience lends authority to what he writes. Winston provides detailed pseudo-code for most of the algorithms discussed, so you will be able to implement and test the algorithms immediately. The book contains exercises to test your knowledge of the subject and helpful introductions and summaries to guide you through the material.
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From the Back Cover
This book explains how it is possible for computers to reason and perceive, thus introducing the field called artificial intelligence. From the book, you learn why the field is important, both as a branch of engineering and as a science. If you are a computer scientist or an engineer, you will enjoy the book, because it provides a cornucopia of new ideas for representing knowledge, using knowledge, and building practical systems. If you are a psychologist, biologist, linguist, or philosopher, you will enjoy the book because it provides an exciting computational perspective on the mystery of intelligence. The Knowledge You Need This completely rewritten and updated edition of Artificial Intelligence reflects the revolutionary progress made since the previous edition was published. Part I is about representing knowledge and about reasoning methods that make use of knowledge. The material covered includes the semantic-net family of representations, describe and match, generate and test, means-ends analysis, problem reduction, basic search, optimal search, adversarial search, rule chaining, the rete algorithm, frame inheritance, topological sorting, constraint propagation, logic, truth maintenance, planning, and cognitive modeling. Part II is about learning, the sine qua non of intelligence. Some methods involve much reasoning; others just extract regularity from data. The material covered includes near-miss analysis, explanation-based learning, knowledge repair, case recording, version-space convergence, identification-tree construction, neural-net training, perceptron convergence, approximation-net construction, and simulated evolution. Part III is about visual perception and language understanding. You learn not only about perception and language, but also about ideas that have been a major source of inspiration for people working in other subfields of artificial intelligence. The material covered includes object identification, stereo vision, shape from shading, a glimpse of modern linguistic theory, and transition-tree methods for building practical natural-language interfaces. Special Features of this Edition Based on extensive teaching experience Semiformal representation and procedure specifications bring the ideas to within a step or two of implementation and highlight unifying themes. Application examples provide a glimpse of the ideas at work in real-world systems. Powerful ideas and principles are identified and emphasized. 0201533774B04062001
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Product details
Paperback: 737 pages
Publisher: Pearson; 3 edition (May 10, 1992)
Language: English
ISBN-10: 0201533774
ISBN-13: 978-0201533774
Product Dimensions:
7.6 x 2 x 9 inches
Shipping Weight: 3 pounds (View shipping rates and policies)
Average Customer Review:
3.9 out of 5 stars
11 customer reviews
Amazon Best Sellers Rank:
#375,686 in Books (See Top 100 in Books)
Some chapters covers great deal of information and it is pretty clear in this book. (R&N information overloads sometimes)Pretty much worth four starts.Example==========================Chapter 21 compared to R&N chapter 18 my opinion is it is better in this book on basic theory.R&N information overloads in most cases it diverts busy reader (working students) getting the basics first.
This book is decent but it is showing its age both in terms of content and style. The theory explored is still relevant and it is a good companion to an AI course.
This book is a timeless classic.
A great intro to the psychology and technology behind AI. Even though the book is 20 some years old, it is a true asset to any mathematician's or programmer's library.Jason R.S.
good
It's too bad that MIT OCW doesn't have a series of video lectures to accompany this textbook. But then again, if the textbook is good enough, it won't need lectures.
New as expected.
Winston's book is really terrible. I mean truly repellently, malignantly bad. "Can it really be as bad as all that?" you wonder. Yes!! It's that bad!! For starters, the book is poorly organized. Topics that logically belong together are often several chapters apart. There is no overall structure to the book. It seems like a collection of topics in AI that were hastily assembled without concern for thematic organization or flow. For example, the forward and backward chaining algorithms are presented in a chapter (Ch. 7) on rule-based systems, but are not even mentioned in the chapter (Ch. 13) on logic! Perceptron training is presented AFTER backpropagation! Contrast this with the much better book by Russell and Norvig, which uses the theme of intelligent agents as a continuing motivation throughout, and which groups related topics into logically arranged chapters.The examples in Winston are atrocious. The main example in the backpropagation chapter is some kind of classification network with a bizarre topography. This example is so trivial and weird that it totally fails to illustrate the strengths of backpropagation. The explanations of generalization and overfitting in backprop training are awful.The only chapter of this book that is not an unmitigated pedagogical disaster is the chapter on genetic algorithms, although better introductions exist (e.g. Melanie Mitchell).A further annoyance is the placement of all the exercises at the end of the book instead of the end of the chapters to which they correspond.Avoid this book. It is truly horrible, and vastly superior books on AI are readily available at comparable prices.
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