Artificial Intelligence: A New Synthesis

by Nils J. Nilsson

Intelligent agents are employed as the central characters in this new introductory text. Beginning with elementary reactive agents, Nilsson gradually increases their cognitive horsepower to illustrate the most important and lasting ideas in AI. Neural networks, genetic programming, computer vision, heuristic search, knowledge representation and reasoning, Bayes networks, planning, and language understanding are each revealed through the growing capabilities of these agents. The book provides a refreshing and motivating new synthesis of the field by one of AI's master expositors and leading researchers. Artificial Intelligence: A New Synthesis takes the reader on a complete tour of this intriguing new world of AI.

Genres: Artificial Intelligence, Computer Science, Technical, Computers

513 pages, Hardcover

First published August 1, 1997

About the author

Nils J. Nilsson is Kumagai Professor of Engineering, Emeritus, in the Department of Computer Science at Stanford University. He is the author of The Quest for Artificial Intelligence: A History of Ideas and Achievements and other books. He lives in Oregon.

Reviews

[Stefan Berteau · Rating 4 out of 5]

A very solid reference guide which covers simple implementations in many different branches associated with AI. It does not deal with fuzzy logic, but has good coverage of the propositional and first order predicate calculuses, feedforward neural networks (but not feedback architectures), bayesian probability inference and bayes nets, and genetic algorithms, among other things. I often use it as a reference when I have to dabble in an area that's new to me.

[Hemanth Kumar · Rating 3 out of 5]

This not so new synthesis is a reference guide rather a textbook. Gives a broad overview of all the things involved in AI. But author fails to pique interest but I feel it's more oriented towards university study rather than casual study.

[Franck Chauvel · Rating 3 out of 5]

This—not really—new synthesis on Artificial Intelligence, remains a good summary. It proceeds gradually, from building simple agents that apply rules to more complicated ones that deduce knowledge, prove, learn, plan and could eventually self-organise.

In my view, it lacks a chapter about control theory, which is also a solution to the "what to do" question and techniques such as Kalman Filters have also their place. I also miss a complete case study that would illustrate how we integrate these techniques (also the last chapter briefly touches upon that).

[Gregor Erbach · Rating 4 out of 5]

Nilsson's book presents all major areas of artificial intelligence from the unifying perspective of the problem of constructing an intelligent agent. Many of the important subfields of AI are introduced, including machine learning. The book is clearly written and can be understood if you have a good knowledge of computer science.