Artificial Intelligence: A Modern Approach / Edition 2

Artificial Intelligence: A Modern Approach / Edition 2

by Stuart Russell, Peter Norvig, Peter Norvig
     
 

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

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Overview

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

Product Details

ISBN-13:
9780137903955
Publisher:
Prentice Hall
Publication date:
02/01/2003
Series:
Prentice Hall Series in Artificial Intelligence
Edition description:
Older Edition
Pages:
1132
Product dimensions:
8.28(w) x 10.14(h) x 1.76(d)

Meet 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 of computer science, director of the Center for Intelligent Systems, 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 cowinner of the Computers and Thought Award. He was a 1996 Miller Professor of the University of California and was appointed to a Chancellor's Professorship in 2000. In 1998, he gave the Forsythe Memorial Lectures at Stanford University. He is a Fellow and former Executive Council member of the American Association for Artificial Intelligence. He has published over 100 papers on a wide range of topics in artificial intelligence. His other books include The Use of Knowledge in Analogy and Induction and (with Eric Wefald) Do the Right Thing: Studies in Limited Rationality.

Peter Norvig is director of Search Quality at Google, Inc. He is a Fellow and Executive Council member of the American Association for Artificial Intelligence. 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. Before that he served as chief scientist at Junglee, where he helped develop one of the first Internet information extraction services, and as a senior scientist at Sun Microsystems Laboratories working on intelligent information retrieval. Hereceived a B.S. in applied mathematics from Brown University and a Ph.D. in computer science from the University of California at Berkeley. He has been a professor at the University of Southern California and a research faculty member at Berkeley. He has over 50 publications in computer science including the books Paradigms of AI Programming: Case Studies in Common Lisp, Verbmobil: A Translation System for Face-to-Face Dialog, and Intelligent Help Systems for UNIX.

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Table of Contents

IArtificial Intelligence
1Introduction1
2Intelligent Agents32
IIProblem-solving
3Solving Problems by Searching59
4Informed Search and Exploration94
5Constraint Satisfaction Problems137
6Adversarial Search161
IIIKnowledge and reasoning
7Logical Agents194
8First-Order Logic240
9Inference in First-Order Logic272
10Knowledge Representation320
IVPlanning
11Planning375
12Planning and Acting in the Real World417
VUncertain knowledge and reasoning
13Uncertainty462
14Probabilistic Reasoning492
15Probabilistic Reasoning over Time537
16Making Simple Decisions584
17Making Complex Decisions613
VILearning
18Learning from Observations649
19Knowledge in Learning678
20Statistical Learning Methods712
21Reinforcement Learning763
VIICommunicating, perceiving, and acting
22Communication790
23Probabilistic Language Processing834
24Perception863
25Robotics901
VIIIConclusions
26Philosophical Foundations947
27AI: Present and Future968
AMathematical background977
BNotes on Languages and Algorithms984
Bibliography987
Index1045

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