Artificial Intelligence
Description
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.
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Person
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 Negnevitsky's 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.
Content
- Introduction to knowledge based intelligent systems
- Rule-based expert systems
- Uncertainty management in rule-based expert systems
- Fuzzy expert systems
- Frame-based expert systems
- Artificial neural networks
- Evolutionary computation
- Hybrid intelligent systems
- Knowledge engineering
- Data mining and knowledge discovery
- Glossary
- Appendix: AI tools and vendors
