Artificial Intelligence A Modern Approach

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

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
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