Elements of ML Programming, ML97 Edition

I. ARTIFICIAL INTELLIGENCE.

1. Introduction.
2. Intelligent Agents.

II. PROBLEM-SOLVING.

3. Solving Problems by Searching.
4. Informed Search and Exploration.
5. Constraint Satisfaction Problems.
6. Adversarial Search.

III. KNOWLEDGE AND REASONING.

7. Logical Agents.
8. First-Order Logic.
9. Inference in First-Order Logic.
10. Knowledge Representation.

IV. PLANNING.

11. Planning.
12. Planning and Acting in the Read World.

V. UNCERTAIN KNOWLEDGE AND REASONING.

13. Uncertainty.
14. Probabilistic Reasoning Systems.
15. Probabilistic Reasoning Over Time.
16. Making Simple Decisions.
17. Making Complex Decisions.

VI. LEARNING.

18. Learning from Observations.
19. Statistical Learning.
20. Reinforcement Learning.
21. Knowledge in Learning.

VII. COMMUNICATING, PERCEIVING, AND ACTING.

22. Agents that Communicate.
23. Text Processing in the Large.
24. Perception.
25. Robotics.

VIII. CONCLUSIONS.

26. Philosophical Foundations.
27. AI: Present and Future.

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