Schedule
| Date | Topic | Reading | Homework |
| W 9/3 | What is AI? What is an agent? | Ch.1,2 | A0 out |
| M 9/8 | Problem-solving agents. Blind search. | Ch.2,3 | |
| W 9/10 | Heuristic search. Local search. | Ch.4 | A1 out |
| M 9/15 | Constraint satisfaction problems. | Ch.5 | A0 due |
| W 9/17 | Games and adversarial search. | Ch.6 | A1 due; A2 out |
| M 9/22 | Logical agents. Propositional logic. | Ch.7 | |
| W 9/24 | Logical inference. First-order logic. | Ch.7,8 | |
| M 9/29 | Inference in First-Order Logic. | Ch.8,9 | A2 due. A3 out. |
| W 10/1 | Knowledge Representation. Intro to Natural Language Processing. | Ch.10, 22.2-3 | |
| M 10/6 | Midterm revision. | A3 due. A4 out. | |
| W 10/8 | Midterm 1 | ||
| M 10/13 | NO CLASS: Columbus Day | ||
| W 10/15 | Planning | Ch.11 | A4 due Friday. A5 out |
| M 10/20 | Uncertain environments. Probabilistic reasoning. | Ch.13,14 | |
| W 10/22 | Approximate inference. Probabilistic reasoning over time. | Ch.15 | A5 due; A6 out |
| M 10/27 | Decison-making under uncertainty. | 16.1-3,16.5,17.1-3 | |
| W 10/29 | Reinforcement learning. | Ch.21 | A6 due; Proposals out |
| M 11/3 | Review of probabilistic reasoning. | Ch.13-17,21 | |
| W 11/5 | Machine learning I. | 18.1-2, 20.1-2 | Proposals due. |
| M 11/10 | Machine learning II. | 20.5 | Start working on your final projects. |
| W 11/12 | Midterm revision. | ||
| M 11/17 | Midterm 2. | ||
| W 11/19 | Guest lecture: Natural Language Processing. Luke Zettlemoyer, MIT | ||
| M 11/24 | Machine vision. | Ch.24 | |
| W 11/26 | NO CLASS (Thanksgiving) | ||
| M 12/1 | Multi-agent AI. Game theory. | Sec.17.6-7 | |
| W 12/3 | Robotics and Behavior-based AI. | Ch.21, papers | |
| M 12/8 | Final project presentations | Project reports due before Monday, Dec 15. |