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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
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
Dr Michael Negnevitsky is a Professor in Electrical Engineering and Computer Science at the University of Tasmania, Australia. The book has developed from his lectures to undergraduates. Educated as an electrical engineer, Dr Negnevitskys many interests include artificial intelligence and soft computing. His research involves the development and application of intelligent systems in electrical engineering, process control and environmental engineering. He has authored and co-authored over 300 research publications including numerous journal articles, four patents for inventions and two books.
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
| Erscheinungsjahr: | 2011 |
|---|---|
| Genre: | Informatik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Seiten: | 504 |
| Inhalt: | Kartoniert / Broschiert |
| ISBN-13: | 9781408225745 |
| ISBN-10: | 1408225743 |
| Sprache: | Englisch |
| Einband: | Kartoniert / Broschiert |
| Autor: | Negnevitsky, Michael |
| Hersteller: | Pearson Education Limited |
| Maße: | 235 x 156 x 30 mm |
| Von/Mit: | Michael Negnevitsky |
| Erscheinungsdatum: | 19.05.2011 |
| Gewicht: | 0,748 kg |
Dr Michael Negnevitsky is a Professor in Electrical Engineering and Computer Science at the University of Tasmania, Australia. The book has developed from his lectures to undergraduates. Educated as an electrical engineer, Dr Negnevitskys many interests include artificial intelligence and soft computing. His research involves the development and application of intelligent systems in electrical engineering, process control and environmental engineering. He has authored and co-authored over 300 research publications including numerous journal articles, four patents for inventions and two books.
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
| Erscheinungsjahr: | 2011 |
|---|---|
| Genre: | Informatik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Seiten: | 504 |
| Inhalt: | Kartoniert / Broschiert |
| ISBN-13: | 9781408225745 |
| ISBN-10: | 1408225743 |
| Sprache: | Englisch |
| Einband: | Kartoniert / Broschiert |
| Autor: | Negnevitsky, Michael |
| Hersteller: | Pearson Education Limited |
| Maße: | 235 x 156 x 30 mm |
| Von/Mit: | Michael Negnevitsky |
| Erscheinungsdatum: | 19.05.2011 |
| Gewicht: | 0,748 kg |
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