Artificial Intelligence: A Modern Approach / Edition 1

Artificial Intelligence: A Modern Approach / Edition 1

by Stuart J. Russell
     
 

ISBN-10: 0131038052

ISBN-13: 9780131038059

Pub. Date: 12/13/1994

Publisher: Prentice Hall Professional Technical Reference

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

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. Knowledge in Learning.
20. Statistical Learning Methods.
21. Reinforcement Learning.

VII. COMMUNICATING, PERCEIVING, AND ACTING.
22. Agents that Communicate.
23. Text Processing in the Large.
24. Perception.
25. Robotics.

VIII. CONCLUSIONS.
26. Philosophical Foundations.
27. AI: Present and Future.

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