Week Date Topics Slides
1 3/17(Tue)  Lecture 1. Introduction
3/19(Thu)  Lecture 2. Intelligent Agents
2 3/24(Tue)  Lecture 3. Problem Solving and Search
3/26(Thu)  Lecture 4. Beyond Classical Search
3 3/31(Tue)  Lecture 5. Adversarial Search
4/2(Thu)  Lecture 6. Logical Agents
 Project 2 Announcement
4 4/7(Tue)  Lecture 7. First-Order Logic
4/9(Thu)  Lecture 8. Inference in First-Order Logic
5 4/14(Tue) Lecture 9. Planning
4/16(Thu)  Lecture 10. Uncertainty and Probability
6 4/21(Tue)  Lecture 11. Bayesian Networks
4/23(Thu)  Lecture 12. Probabilitic Reasoning over Time
7 4/28(Tue)  Midterm
4/30(Thu)  Holiday
8 5/5(Tue)  Holiday
5/7(Thu)  Lecture 13. Temporal Probability Models
9 5/12(Tue)  Lecture 14. Markov Decision Processes
5/14(Thu)  Lecture 15. Learning from Examples
10 5/19(Tue)  Lecture 16. Deep Neural Networks
5/21(Thu)  Lecture 17. Knowledge in Learning
11 5/26(Tue)   Lecture 18. Learning Probabilistic Models
5/28(Thu)  Lecture 19. Reinforcement Learning
12 6/2(Tue)  Lecture 20. Language
6/4(Thu)  Lecture 21. Vision
13 6/9(Tue)   Lecture 22. Robotics
6/11(Thu)  Lecture 23. Human Level AI
14 6/16(Tue)  Final exam
6/23(Tue)  Project 2 Poster Presentation