Our beliefs constitute a large part of our knowledge of the world. We have beliefsabout objects, about culture, about the past, and about the future. We have beliefs about otherpeople, and we believe that they have beliefs as well. We use beliefs to predict, to explain, tocreate, to console, to entertain. Some of our beliefs we call theories, and we are extraordinarilycreative at constructing them. Theories of quantum mechanics, evolution, and relativity areexamples. But so are theories about astrology, alien abduction, guardian angels, and reincarnation.All are products (with varying degrees of credibility) of fertile minds trying to find explanationsfor observed phenomena. In this book, Nils Nilsson examines beliefs: what they do for us, how wecome to hold them, and how to evaluate them. We should evaluate our beliefs carefully, Nilssonpoints out, because they influence so many of our actions and decisions. Some of our beliefs aremore strongly held than others, but all should be considered tentative and changeable. Nilsson showsthat beliefs can be quantified by probability, and he describes networks of beliefs in which theprobabilities of some beliefs affect the probabilities of others. He argues that we can evaluate ourbeliefs by adapting some of the practices of the scientific method and by consulting expert opinion.And he warns us about "belief traps" -- holding onto beliefs that wouldn't survivecritical evaluation. The best way to escape belief traps, he writes, is to expose our beliefs to thereasoned criticism of others.

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.

* An evolutionary approach provides a unifying theme
* Thorough coverage of important AI ideas, old and new
* Frequent use of examples and illustrative diagrams
* Extensive coverage of machine learning methods throughout the text
* Citations to over 500 references
* Comprehensive index