Artificial Intelligence

A Guide to Intelligent Systems

Michael Negnevitsky

415 pages, parution le 30/09/2004 (2^eme édition)

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Résumé

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 systems,
knowledge engineering,
data mining.

In a university setting the book can be used as an introductory course within computer science, information systems or engineering departments. The book is also suitable as a self-study guide for non-computer science professionals, giving access to the state of the art in knowledge-based systems and computational intelligence. Everyone who faces challenging problems and cannot solve them using traditional approaches can benefit

Sommaire

Introduction to Knowledge-base Intelligent Systems
Rule-Based Expert Systems
Uncertainty Management in Rule-Based Expert Systems
Fuzzy Expert Systems
Frame-Based ExpertSystems
Artificial Neural Networks
Evolutionary Computation
Hybrid Intelligent Systems
Knowledge Engineering and Data Mining

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Addison Wesley
Auteur(s)	Michael Negnevitsky
Parution	30/09/2004
Édition	2^eme édition
Nb. de pages	415
Format	16 x 24
Couverture	Relié
Poids	780g
Intérieur	Noir et Blanc
EAN13	9780321204660
ISBN13	978-0-321-20466-0