Artificial Intelligence: A Modern Approach (2nd Edition)

Artificial Intelligence: A Modern Approach introduces basic ideas in artificial intelligence from the perspective of building intelligent agents, which the authors define as “anything that can be viewed as perceiving its environment through sensors and acting upon the environment through effectors.” This textbook is up-to-date and is organized using the latest principles of good textbook design. It includes historical notes at the end of every chapter, exercises, margin notes, a bibliography, and a competent index. Artificial Intelligence: A Modern Approach covers a wide array of material, including first-order logic, game playing, knowledge representation, planning, and reinforcement learning.

Stuart J. Russell, Peter Norvig
Artificial Intelligence: A Modern Approach (2nd Edition)
Prentice Hall (December 20, 2002)
ISBN: 0137903952

Table of contents

- Part I Artificial Intelligence
  - - 1 Introduction
  - 2 Intelligent Agents

- Part II Problem Solving
  - - 3 Solving Problems by Searching
  - - 4 Informed Search and Exploration
  - - 5 Constraint Satisfaction Problems (pdf)
  - 6 Adversarial Search

- Part III Knowledge and Reasoning
  - - 7 Logical Agents (pdf)
  - - 8 First-Order Logic
  - - 9 Inference in First-Order Logic
  - 10 Knowledge Representation

- Part IV Planning
  - - 11 Planning (pdf)
  - 12 Planning and Acting in the Real World

- Part V Uncertain Knowledge and Reasoning
  - - 13 Uncertainty
  - - 14 Probabilistic Reasoning
  - - 15 Probabilistic Reasoning Over Time
  - - 16 Making Simple Decisions
  - 17 Making Complex Decisions

- Part VI Learning
  - - 18 Learning from Observations
  - - 19 Knowledge in Learning
  - - 20 Statistical Learning Methods (pdf)
  - 21 Reinforcement Learning

- Part VII Communicating, Perceiving, and Acting
  - - 22 Communication
  - - 23 Probabilistic Language Processing
  - - 24 Perception
  - 25 Robotics

Part VIII Conclusions
- - 26 Philosophical Foundations
- 27 AI: Present and Future

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