Artificial Intelligence: A Modern Approach, 2/E



Artificial Intelligence: A Modern Approach, 2/E

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.

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Introduction to the Theory of Computation



Introduction to the Theory of Computation

This highly anticipated revision of Michael Sipser’s popular text builds upon the strengths of the previous edition. It tells the fascinating story of the theory of computation-a subject with beautiful results and exciting unsolved questions at the crossroads of mathematics and computer science. Sipser’s candid, crystal-clear style allows students at every level to understand and enjoy this field. His innovative “proof idea” sections reveal the intuition underpinning the formal proofs of theorems by explaining profound concepts in plain English. The new edition incorporates many improvements students and professors have suggested over the years and offers completely updated, classroom-tested problem sets with sample solutions at the end of each chapter. Book jacket.