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Artificial intelligence : a guide to intelligent systems / Michael Negnevitsky

By: Negnevitsky, Michael
Material type: TextTextPublisher: New York : Addison-Wesley; 2005Edition: 2nd edDescription: xiv, 415 pISBN: 9780321204660Subject(s): Artificial intelligencDDC classification: 006.3 Online resources: Click here to access online
Contents:
Table of contents : 1. Introduction to knowledge-based intelligent systems -- 2. Rule-based expert systems -- 3. Uncertainty management in rule-based expert systems -- 4. Fuzzy expert systems -- 5. Frame-based expert systems -- 6. Artificial neutral networks -- 7. Evolutionary computation -- 8. Hybrid intelligent systems -- 9. Knowledge engineering and data mining.
In: Pearson eBooksSummary: Summary : Keeping the maths to a minimum, Negnevitsky explains the principles of AI, demonstrates how systems are built, what they are useful for and how to choose the right tool for the job.
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Table of contents :
1. Introduction to knowledge-based intelligent systems --
2. Rule-based expert systems --
3. Uncertainty management in rule-based expert systems --
4. Fuzzy expert systems --
5. Frame-based expert systems --
6. Artificial neutral networks --
7. Evolutionary computation --
8. Hybrid intelligent systems --
9. Knowledge engineering and data mining.

Summary :
Keeping the maths to a minimum, Negnevitsky explains the principles of AI, demonstrates how systems are built, what they are useful for and how to choose the right tool for the job.

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