Artificial Intelligence: A Guide to Intelligent Systems

by Michael Negnevitsky

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. However, available tools and their uses are described, and program examples are given in Java. 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, particularly in intelligent agents and knowledge discovery.

Genres: Artificial Intelligence

500 pages, Paperback

First published January 1, 2005

Reviews

[Bulu Iraddim · Rating 4 out of 5]

As an aspiring PhD candidate in Behavioral Economics and AI, I found Artificial Intelligence: A Guide to Intelligent Systems by Michael Negnevitsky to be an excellent resource. The book provides a comprehensive yet accessible exploration of AI concepts, from machine learning to expert systems, with a focus on practical applications. It’s particularly valuable for understanding how AI can model and influence human behavior—an area directly relevant to my research.

Negnevitsky’s clear explanations and case studies help bridge the gap between theory and real-world applications, while also addressing the ethical and social implications of AI. Although the book can be technical at times, it offers a solid foundation for anyone interested in the intersection of AI, economics, and human behavior.