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I Artificial Intelligence
1 Introduction ... 19
2 Intelligent Agents ... 54
II Problem-solving
3 Solving Problems by Searching ... 81
4 Search in Complex Environments ... 128
5 Constraint Satisfaction Problems ... 164
6 Adversarial Search and Games ... 192
III Knowledge, reasoning, and planning
7 Logical Agents ... 226
8 First-Order Logic ... 269
9 Inference in First-Order Logic ... 298
10 Knowledge Representation ... 332
11 Automated Planning ... 362
IV Uncertain knowledge and reasoning
12 Quantifying Uncertainty ... 403
13 Probabilistic Reasoning ... 430
14 Probabilistic Reasoning over Time ... 479
15 Making Simple Decisions ... 518
16 Making Complex Decisions ... 552
17 Multiagent Decision Making ... 589
18 Probabilistic Programming ... 641
V Machine Learning
19 Learning from Examples ... 669
20 Knowledge in Learning ... 739
21 Learning Probabilistic Models ... 772
22 Deep Learning ... 801
23 Reinforcement Learning ... 840
VI Communicating, perceiving, and acting
24 Natural Language Processing ... 874
25 Deep Learning for Natural Language Processing ... 907
26 Robotics ... 932
27 Computer Vision ... 988
VII Conclusions
28 Philosophy, Ethics, and Safety of AI ... 1032
29 The Future of AI ... 1063
Appendix A: Mathematical Background ... 1074
Appendix B: Notes on Languages and Algorithms ... 1081
Bibliography ... 1084
Index ... 1119

The long-anticipated revision of Artificial Intelligence: A Modern Approach explores the full breadth and depth of the field of artificial intelligence (AI). The 4th Edition brings readers up to date on the latest technologies, present concepts in a more unified manner, and offers new or expanded coverage of machine learning, deep learning, transfer learning, multi agent systems, robotics, natural language processing, causality, probabilistic programming, privacy, fairness, and safe AI.