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Artificial Intelligence : A Guide to Intelligent Systems by Michael Negnevitsky (2011, Trade Paperback)

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Aperback: 504 pages. US Edition. ISBN-13: 978-1408225745.

About this product

Product Identifiers

PublisherPearson Education, The Limited

ISBN-101408225743

ISBN-139781408225745

eBay Product ID (ePID)109591556

Product Key Features

Number of Pages504 Pages

Publication NameArtificial Intelligence : a Guide to Intelligent Systems

LanguageEnglish

SubjectExpert Systems, Intelligence (Ai) & Semantics

Publication Year2011

FeaturesRevised

TypeTextbook

AuthorMichael Negnevitsky

Subject AreaComputers

FormatTrade Paperback

Dimensions

Item Height1 in

Item Weight26.2 Oz

Item Length8.7 in

Item Width6.3 in

Additional Product Features

Edition Number3

LCCN2010-041988

Dewey Edition22

ReviewsThis book covers many areas related to my module. I would be happy to recommend this book to my students. I believe my students would be able to follow this book without any difficulty. Book chapters are very well organised and this will help me to pick and choose the subjects related to this module.”Dr Ahmad Lotfi, Nottingham Trent University, UK, "This book covers many areas related to my module. I would be happy to recommend this book to my students. I believe my students would be able to follow this book without any difficulty. Book chapters are very well organised and this will help me to pick and choose the subjects related to this module." Dr Ahmad Lotfi, Nottingham Trent University, UK

IllustratedYes

Dewey Decimal006.3

Edition DescriptionRevised edition

Table Of ContentContents Preface xii New to this edition xiii Overview of the book xiv Acknowledgements xvii 1 Introduction to knowledge-based intelligent systems 1 1.1 Intelligent machines, or what machines can do 1 1.2 The history of artificial intelligence, or from the ''Dark Ages'' to knowledge-based systems 4 1.3 Summary 17 Questions for review 21<

SynopsisNegnevitsky shows students how to build intelligent systems drawing on techniques from knowledge-based systems, neural networks, fuzzy systems, evolutionary computation and now also intelligent agents. The principles behind these techniques are explained without resorting to complex mathematics, showing how the various techniques are implemented, when they are useful and when they are not. No particular programming language is assumed and the book does not tie itself to any of the software tools available. However, available tools and their uses are described, and program examples are given in Java. The lack of assumed prior knowledge makes this book ideal for any introductory courses in artificial intelligence or intelligent systems design, while the contemporary coverage means more advanced students will benefit by discovering the latest state-of-the-art techniques, particularly in intelligent agents and knowledge discovery., Artificial Intelligence is one of the most rapidly evolving subjects within the computing/engineering curriculum, with an emphasis on creating practical applications from hybrid techniques. Despite this, the traditional textbooks continue to expect mathematical and programming expertise beyond the scope of current undergraduates and focus on areas not relevant to many of today's courses. Negnevitsky shows students how to build intelligent systems drawing on techniques from knowledge-based systems, neural networks, fuzzy systems, evolutionary computation and now also data mining. The principles behind these techniques are explained without resorting to complex mathematics, showing how the various techniques are implemented, when they are useful and when they are not. No particular programming language is assumed and the book does not tie itself to any of the software tools available. However, available tools and their uses will be described and program examples will be given in MATLAB. The lack of assumed prior knowledge makes this book ideal for any introductory courses in artificial intelligence or intelligent systems design, while the contemporary coverage means more advanced students will benefit by discovering the latest state-of-the-art techniques. The book covers: Rule-based expert systems Fuzzy expert systems Frame-based expert systems Artificial neural networks Evolutionary computation Hybrid intelligent systems Knowledge engineering Data mining

LC Classification NumberQA76.76.E95N445 2010