| Mon | Day | DOW | Special | Class | Lecture | Unit | Topic | AIMA (4th ed) | Project | AIMA (3rd ed) | Poole & Mackworth (2nd ed) |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 8 | 31 | R | 1 | 0 | Intro | 1 | 1 | ||||
| 9 | 5 | T | 2 | 1.1 | Search | Problem Solving | 3.0-3.3.3 | 3.0-3.3.1 | 3.1-3.4 | ||
| 9 | 7 | R | 3 | 1.2 | Search Strategies | 3.3.4-3.6.1 | 3.3.2-3.6.1 | 3.5-3.6 | |||
| 9 | 12 | T | 4 | 1.3 | Adversarial Search | 5.0-5.2.1 | 5.0-5.2.1 | 11.0-11.3 | |||
| 9 | 14 | R | 5 | 1.4 | Adversarial Search 2 | 5.3-5.3.2; 5.5-5.6; 5.7 fyi | 5.3-5.4.2; 5.5-5.6; 5.7-5.9 fyi | ||||
| 9 | 19 | T | 6 | 1.5 | Local Search | 4.0-4.1 | 4.0-4.1 | 4.7 | |||
| 9 | 21 | R | 7 | 1.6 | Local Search 2 | 4.3-4.4; 4.2, 4.5 fyi | 4.3-4.4; 4.2, 4.5 fyi | ||||
| 9 | 25 | M | Project 1 due | ||||||||
| 9 | 26 | T | 8 | Exam 1 | |||||||
| 9 | 28 | R | 9 | 2.1 | Representation | Constraint Satisfaction | 6.0-6.4 | 6.0-6.4 | 4.0-4.6 | ||
| 10 | 3 | T | 10 | 2.2 | Propositional Logic | 7.0-7.4 | 7.0-7.4 | 5.0-5.1 | |||
| 10 | 5 | R | 11 | 2.3 | Propositional Theorem Proving | 7.5 | 7.5 | 5.2-5.3 | |||
| 10 | 10 | T | 12 | 2.4 | First-Order Logic | 8.0-8.3 | 8.0-8.3 | 13.0-13.3 | |||
| 10 | 12 | R | 13 | 2.5 | First-Order Theorem Proving | 9 | 9 | 13.4-13.5 | |||
| 10 | 17 | T | Fall Break | ||||||||
| 10 | 18 | W | Project 2 due | ||||||||
| 10 | 19 | R | 14 | Exam 2 | |||||||
| 10 | 24 | T | 15 | 3.1 | Uncertainty | Representing Uncertainty | 12.0-12.2; 12.2.3 fyi | 13.0-13.2; 13.2.3 fyi | 8.0-8.2 | ||
| 10 | 26 | R | 16 | 3.2 | Uncertain Inference | 12.3-12.7 | 13.3-13.6 | ||||
| 10 | 31 | T | 17 | 3.3 | Bayesian Networks | 13.0-13.2.1; 13.3-.3 | 14.0-14.2, 14.4-14.4.3 | 8.3-8.4 | |||
| 11 | 2 | R | 18 | 3.4 | Approximate Inference in Bayesian Networks | 13.4; 13.5 fyi | 14.5; 14.7 fyi | 8.6 | |||
| 11 | 7 | T | 19 | 3.5 | Inference in Temporal Models | 14.0-14.2; 14.3 fyi | 15.0-15.2; 15.3 fyi | 8.5 | |||
| 11 | 8 | W | Project 3 due | ||||||||
| 11 | 9 | R | 20 | Exam 3 | |||||||
| 11 | 14 | T | 21 | 4.1 | Learning | Learning From Examples, Decision Trees | 19.0-19.3, 19.4.0 | 18.0-18.3, 18.4.0 | 7.0-7.3.1 | ||
| 11 | 16 | R | 22 | 4.2 | Linear Regression and Linear Classifiers | 19.6 | 18.6 | 7.3.2-7.4 | |||
| 11 | 21 | T | 23 | TBD | TBD | TBD | |||||
| 11 | 23 | R | Thanksgiving | ||||||||
| 11 | 28 | T | 24 | 4.3 | Neural Networks | 21.0-21.2 | 18.7-18.7.4 | 7.5 | |||
| 11 | 30 | R | 25 | 4.4 | Learning Probabilistic Models | 20.0-20.2.2; 20.2.7 fyi | 20.0-20.2.2; 20.2.5 fyi | 10.3-10.3.1 | |||
| 12 | 5 | T | 26 | 4.5 | Learning with Incomplete Data | 20.3.0, 20.3.4 | 20.3.0, 20.3.4 | 10.3.2-10.3.3 | |||
| 12 | 6 | W | Project 4 due | ||||||||
| 12 | 7 | R | 27 | Exam 4 | |||||||
| 12 | 12 | T | 28 | TBD | TBD | TBD |
Last change: Thu Oct 19 10:24:53 2023