Artificial intelligence: a modern approach

I. Artificial Intelligence. 1. Introduction ; 2. Intelligent Agents

II. Problem-solving. 3. Solving Problems by Searching ; 4. Search in Complex Environments ; 5. Adversarial Search and Games ; 6. Constraint Satisfaction Problems

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. Probabilistic Programming ; 16. Making Simple Decisions ; 17. Making Complex Decisions ; 18. Multiagent Decision Making

V. Machine Learning. 19. Learning from Examples ; 20. Learning Probabilistic Models ; 21. Deep Learning ; 22. Reinforcement Learning

VI. Communicating, Perceiving, and Acting. 23. Natural Language Processing ; 24. Deep Learning for Natural Language Processing ; 25. Computer Vision

26. Robotics

VII. Conclusion. 27. Philosophy and Ethics of AI ; 28. The Future of AI

A. Mathematical Background

B. Notes on Language and Algorithms.