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
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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
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