Artificial Intelligence: A Modern Approach, 4th Global ed.

by Stuart Russell and Peter Norvig

The authoritative, most-used AI textbook, adopted by over 1500 schools.

Table of Contents for the Global Edition (or see the US Edition)

    Preface (pdf); Contents with subsections (pdf)
I Artificial Intelligence
    1 Introduction
    2 Intelligent Agents
II Problem-solving
    3 Solving Problems by Searching
    4 Search in Complex Environments
    5 Constraint Satisfaction Problems
    6 Adversarial Search and Games
III Knowledge, reasoning, and planning
    7 Logical Agents
    8 First-Order Logic
    9 Inference in First-Order Logic
    10 Knowledge Representation
    11 Automated Planning
IV Uncertain knowledge and reasoning
    12 Quantifying Uncertainty
    13 Probabilistic Reasoning
    14 Probabilistic Reasoning over Time
    15 Making Simple Decisions
    16 Making Complex Decisions
    17 Multiagent Decision Making
    18 Probabilistic Programming

V Machine Learning
    19 Learning from Examples
    20 Knowledge in Learning
    21 Learning Probabilistic Models
    22 Deep Learning
    23 Reinforcement Learning
VI Communicating, perceiving, and acting
    24 Natural Language Processing
    25 Deep Learning for Natural Language Processing
    26 Robotics
    27 Computer Vision
VII Conclusions
    28 Philosophy, Ethics, and Safety of AI
    29 The Future of AI
    Appendix A: Mathematical Background
    Appendix B: Notes on Languages and Algorithms
    Bibliography (pdf and LaTeX .bib file and bib data)
    Index (pdf)

    Exercises (website)
    Figures (pdf)
    Code (website); Pseudocode (pdf)
    Covers: US, Global