Artificial Intelligence: A Modern Approach / Edition 3

by Stuart Russell, Peter Norvig

Overview

The long-anticipated revision of this best-selling book offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Intelligent Agents. Solving Problems by Searching. Informed Search Methods. Game Playing. Agents that Reason Logically. First-order Logic. Building a Knowledge Base. Inference in First-Order Logic. Logical Reasoning Systems. Practical Planning. Planning and Acting. Uncertainty. Probabilistic Reasoning Systems. Making Simple Decisions. Making Complex Decisions. Learning from Observations. Learning with Neural Networks. Reinforcement Learning. Knowledge in Learning. Agents that Communicate. Practical Communication in English. Perception. Robotics. For those interested in artificial intelligence.

Product Details

ISBN-13:	9780136042594
Publisher:	Pearson Education
Publication date:	12/01/2009
Series:	Prentice Hall Series in Artificial Intelligence
Edition description:	Older Edition
Pages:	1152
Product dimensions:	8.30(w) x 10.10(h) x 1.80(d)

About the Author

Stuart Russell was born in 1962 in Portsmouth, England. He received his B.A. with first-class honours in physics from Oxford University in 1982, and his Ph.D. in computer science from Stanford in 1986. He then joined the faculty of the University of California at Berkeley, where he is a professor and former chair of computer science, director of the Center for Human-Compatible AI, and holder of the Smith–Zadeh Chair in Engineering. In 1990, he received the Presidential Young Investigator Award of the National Science Foundation, and in 1995 he was co-winner of the Computers and Thought Award. He is a Fellow of the American Association for Artificial Intelligence, the Association for Computing Machinery, and the American Association for the Advancement of Science, and Honorary Fellow of Wadham College, Oxford, and an Andrew Carnegie Fellow. He held the Chaire Blaise Pascal in Paris from 2012 to 2014. He has published over 300 papers on a wide range of topics in artificial intelligence. His other books include: The Use of Knowledge in Analogy and Induction, Do the Right Thing: Studies in Limited Rationality (with Eric Wefald), and Human Compatible: Artificial Intelligence and the Problem of Control.

Peter Norvig is currently Director of Research at Google, Inc., and was the director responsible for the core Web search algorithms from 2002 to 2005. He is a Fellow of the American Association for Artificial Intelligence and the Association for Computing Machinery. Previously, he was head of the Computational Sciences Division at NASA Ames Research Center, where he oversaw NASA’s research and development in artificial intelligence and robotics, and chief scientist at Junglee, where he helped develop one of the first Internet information extraction services. He received a B.S. in applied mathematics from Brown University and a Ph.D. in computer science from the University of California at Berkeley. He received the Distinguished Alumni and Engineering Innovation awards from Berkeley and the Exceptional Achievement Medal from NASA. He has been a professor at the University of Southern California and a research faculty member at Berkeley. His other books are: Paradigms of AI Programming: Case Studies in Common Lisp, Verbmobil: A Translation System for Face-to-Face Dialog, and Intelligent Help Systems for UNIX.

The two authors shared the inaugural AAAI/EAAI Outstanding Educator award in 2016.

Table of Contents

I. ARTIFICIAL INTELLIGENCE.

1. Introduction.
2. Intelligent Agents.

II. PROBLEM-SOLVING.

3. Solving Problems by Searching.
4. Informed Search and Exploration.
5. Constraint Satisfaction Problems.
6. Adversarial Search.

III. KNOWLEDGE AND REASONING.

7. Logical Agents.
8. First-Order Logic.
9. Inference in First-Order Logic.
10. Knowledge Representation.

IV. PLANNING.

11. Planning.
12. Planning and Acting in the Read World.

V. UNCERTAIN KNOWLEDGE AND REASONING.

13. Uncertainty.
14. Probabilistic Reasoning Systems.
15. Probabilistic Reasoning Over Time.
16. Making Simple Decisions.
17. Making Complex Decisions.

VI. LEARNING.

18. Learning from Observations.
19. Statistical Learning.
20. Reinforcement Learning.
21. Knowledge in Learning.

VII. COMMUNICATING, PERCEIVING, AND ACTING.

22. Agents that Communicate.
23. Text Processing in the Large.
24. Perception.
25. Robotics.

VIII. CONCLUSIONS.

26. PhilosophicalFoundations.
27. AI: Present and Future.

Editorial Reviews

04/01/2015
In its various editions, this has been the standard text on AI for two decades. It has been translated into Japanese, Hungarian, and Russian and covers basics including knowledge representation, learning, and natural-language processing. Russell has published more than 150 papers on AI, and Norvig, formerly of NASA, is now director of research at Google.

Library Journal

a text primarily intended for use in an undergraduate course or course sequence. It shows how intelligent agents can be built using AI methods and explains how different agent designs are appropriate depending on the nature of the task and environment. It uses examples and exercises to lead students from simple reactive agents to advanced planning agents with natural language capabilities. Annotation c. Book News, Inc., Portland, OR (booknews.com)

Booknews