Artificial intelligence : a guide to intelligent systems /
Michael Negnevitsky.
- 1st ed.
- New York : Addison Wesley, 2002.
- xiv, 394 p. : ill. ; 24 cm.
Includes bibliographical references and index.
Virtually all the literature on artificial intelligence is expressed in the jargon of commuter science, crowded with complex matrix algebra and differential equations. Unlike many other books on computer intelligence, this one demonstrates that most ideas behind intelligent systems are simple and straightforward. The book has evolved from lectures given to students with little knowledge of calculus, and the reader needs no prerequisites associated with knowledge of any programming language. The methods used in the book have been extensively tested through several courses given by the author. The book provides an introduction to the field of computer intelligence, covering rule-based expert systems, fuzzy expert systems, frame-based expert systems, artificail neural networks, evolutionary computation, hybrid intelligent system, knowledge engineering, data mining.