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Russell , Norvig , "Artificial Intelligence: A Modern Approach" (2nd Edition)

The first edition of Artificial Intelligence: A Modern Approach has become a classic in the AI literature. It has been adopted by over 600 universities in 60 countries, and has been praised as the definitive synthesis of the field.In the second edition, every chapter has been extensively rewritten.Significant new material has been introduced to cover areas such as constraint satisfaction, fast propositional inference, planning graphs, internet agents, exact probabilistic inference, Markov Chain Monte Carlo techniques, Kalman filters, ensemble learning methods, statistical learning, probabilistic natural language models, probabilistic robotics, and ethical aspects of AI.

The book is supported by a suite of online resources including source code, figures, lecture slides, a directory of over 800 links to "AI on the Web," and an online discussion group. All of this is available at:aima.cs.berkeley.edu

The book is divided into eight parts. Part I, Artificial Intelligence, offers a view of the AI enterprise based around the idea of intelligent agents—systems that can decide what to do and then do it. Part II, Problem Solving, concentrates on methods for deciding what to do when one needs to think ahead several steps—for example in navigating across a country or playing chess. Part III, Knowledge and Reasoning, discusses ways to represent knowledge about the world—how it works, what it is currently like, and what one's actions might do—and how to reason logically with that knowledge. Part IV, Planning, then discusses how to use these reasoning methods to decide what to do, particularly by constructing plans. Part V, Uncertain Knowledge and Reasoning, is analogous to Parts III and IV, but it concentrates on reasoning and decision making in the presence of uncertainty about the world, as might be faced, for example, by a system for medical diagnosis and treatment.Part VI, Learning, describes methods for generating the knowledge required by these decision-making components. Part VII, Communicating, Perceiving, and Acting, describes ways in which an intelligent agent can perceive its environment so as to know what is going on, whether by vision, touch, hearing, or understanding language, and ways in which it can turn its plans into real actions, either as robot motion or as natural language utterances. Finally, Part VIII, Conclusions, analyzes the past and future of AI and the philosophical and ethical implications of artificial intelligence

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