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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 introductory textbook is up-to-date and is organized using the latest principles of good textbook design.

Table of contents

Part I Artificial Intelligence
     1 Introduction
     2 Intelligent Agents
Part II Problem Solving
     3 Solving Problems by Searching
     4 Beyond Classical Search
     5 Adversarial Search
     6 Constraint Satisfaction Problems
Part III Knowledge and Reasoning
     7 Logical Agents
     8 First-Order Logic
     9 Inference in First-Order Logic
    10 Classical Planning
    11 Planning and Acting in the Real World
    12 Knowledge Representation
Part IV Uncertain Knowledge and Reasoning
    13 Quantifying Uncertainty
    14 Probabilistic Reasoning
    15 Probabilistic Reasoning over Time
    16 Making Simple Decisions
    17 Making Complex Decisions
Part V Learning
    18 Learning from Examples
    19 Knowledge in Learning
    20 Learning Probabilistic Models
    21 Reinforcement Learning
Part VII Communicating, Perceiving, and Acting
    22 Natural Language Processing
    23 Natural Language for Communication
    24 Perception
    25 Robotics
Part VIII Conclusions
    26 Philosophical Foundations
    27 AI: The Present and Future
     A Mathematical Background
     B Notes on Languages and Algorithms