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

by Stuart Russell and Peter Norvig

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

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

    Preface (pdf); Contents with subsections
I Artificial Intelligence
    1 Introduction ... 1
    2 Intelligent Agents ... 36
II Problem-solving
    3 Solving Problems by Searching ... 63
    4 Search in Complex Environments ... 110
    5 Adversarial Search and Games ... 146
    6 Constraint Satisfaction Problems ... 180
III Knowledge, reasoning, and planning
    7 Logical Agents ... 208
    8 First-Order Logic ... 251
    9 Inference in First-Order Logic ... 280
    10 Knowledge Representation ... 314
    11 Automated Planning ... 344
IV Uncertain knowledge and reasoning
    12 Quantifying Uncertainty ... 385
    13 Probabilistic Reasoning ... 412
    14 Probabilistic Reasoning over Time ... 461
    15 Probabilistic Programming ... 500
    16 Making Simple Decisions ... 528
    17 Making Complex Decisions ... 562
    18 Multiagent Decision Making ... 599

V Machine Learning
    19 Learning from Examples ... 651
    20 Learning Probabilistic Models ... 721
    21 Deep Learning ... 750
    22 Reinforcement Learning ... 789
VI Communicating, perceiving, and acting
    23 Natural Language Processing ... 823
    24 Deep Learning for Natural Language Processing ... 856
    25 Computer Vision ... 881
    26 Robotics ... 925
VII Conclusions
    27 Philosophy, Ethics, and Safety of AI ... 981
    28 The Future of AI ... 1012
    Appendix A: Mathematical Background ... 1023
    Appendix B: Notes on Languages and Algorithms ... 1030
    Bibliography ... 1033 (pdf and LaTeX .bib file and bib data)
    Index ... 1069 (pdf)

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