Artificial Intelligence: A Modern Approach / Edition 1

Artificial Intelligence: A Modern Approach / Edition 1

by Stuart J. Russell
     
 

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

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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

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Product Details

ISBN-13:
9780131038059
Publisher:
Prentice Hall Professional Technical Reference
Publication date:
12/13/1994
Series:
Prentice Hall Series in Artificial Intelligence
Edition description:
Older Edition
Pages:
912
Product dimensions:
7.80(w) x 9.55(h) x 1.54(d)

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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