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Künstliche Intelligenz: Ein Leitfaden für intelligente Systeme 3E von Negnevitsky
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Standort: PUCHONG, SELANGOR, Malaysia
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Artikelmerkmale
- Artikelzustand
- Version
- US Edition
- Book Format
- Origal Binding
- Print Quality
- High Quality Printed
- ISBN
- 9781408225745
Über dieses Produkt
Product Identifiers
Publisher
Pearson Education, The Limited
ISBN-10
1408225743
ISBN-13
9781408225745
eBay Product ID (ePID)
109591556
Product Key Features
Number of Pages
504 Pages
Language
English
Publication Name
Artificial Intelligence : a Guide to Intelligent Systems
Subject
Expert Systems, Intelligence (Ai) & Semantics
Publication Year
2011
Features
Revised
Type
Textbook
Subject Area
Computers
Format
Trade Paperback
Dimensions
Item Height
1 in
Item Weight
26.2 Oz
Item Length
8.7 in
Item Width
6.3 in
Additional Product Features
Edition Number
3
LCCN
2010-041988
Reviews
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, "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
Dewey Edition
22
Illustrated
Yes
Dewey Decimal
006.3
Edition Description
Revised edition
Table Of Content
Contents 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<
Synopsis
Negnevitsky 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 Number
QA76.76.E95N445 2010
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