Class |
Date |
Topic |
Reading |
Homework |
Comments |
| 1 | Th 8/30 | Course overview; What is AI? | Ch. 1; Lisp Ch. 1; McCarthy paper | HW1(PW) out | Lisp "cheat sheet"
Survey Slides |
| 2 | Tu 9/4 | Agents/Lisp | Ch. 2; Lisp Ch. 2-3; Graham article | Survey due | Slides |
| 3 | Th 9/6 | Problem solving as search; Lisp | Ch. 3.1-3.3; Lisp Ch. 4-5, App. A | Slides | |
| 4 | Tu 9/11 | Uninformed search | Ch. 3.4 | Slides
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| 5 | Th 9/13 | Informed search | Ch. 3.5-3.7, Lisp Ch. 7 | HW1 due; HW2(PW) out |
Slides |
| 6 | Tu 9/18 | Local search, genetic algorithms | Ch. 4.1-4.2 |
Slides
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| 7 | Th 9/20 | Constraint satisfaction | Ch. 6; Vipin Kumar, "Algorithms for Constraint Satisfaction Problems: A Survey" | Slides | |
| 8 | Tu 9/25 | Game playing | Ch. 5 | Slides
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| 9 | Th 9/27 | Game theory | Slides | ||
| 10 | Tu 10/2 | Knowledge-based agents; start propositional logic | Ch. 7.1-7.3 | Project description out | Slides |
| 11 | Th 10/4 | Propositional logic | Ch. 7.4-7.8, 8 | HW2 Due; HW3 out |
Slides |
| 12 | Tu 10/9 | First-order logic | Ch. 9 | Project teams formed | Slides |
| 13 | Th 10/11 | Logical inference | Slides | ||
| 14 | Tu 10/16 | Logical inference, continued; knowledge representation | Ch. 12.1-12.2, 12.5-12.6 | HW3 due; HW4 out |
Slides |
| 15 | Th 10/18 | Philosophy and history of AI |
Turing article Searle article Summary of Kurzweil's book Kevin Kelly's critique |
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| 16 | Tu 10/23 | Midterm Review Day | |||
| 17 | Th 10/25 | MIDTERM (covers material through class #14) |
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| 18 | Tu 10/30 | -Lost to Hurricane Sandy- | |||
| 19 | Th 11/1 | Planning | Ch. 13 | HW4 due | Slides |
| 20 | Tu 11/6 | Partial-order planning and Probabilistic reasoning | HW5(W) out | Slides | |
| 21 | Th 11/8 | Bayesian networks | Ch. 14.1-14.4 | Project design due | Slides |
| 22 | Tu 11/13 | Machine Learning I: Decision Trees | Ch. 18.1-18.4 | Slides | |
| 23 | Th 11/15 | Machine learning II: K-nearest neighbor, naive Bayes, learning Bayes nets | Ch. 20.1-20.2 | Extra Credit Assignment out | Slides
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| 24 | Tu 11/20 | Guest Lecture: Dr. Marie desJardins Preference Learning |
HW5 due | Slides Mastermind Code |
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| Th 11/22 | Happy Thanksgiving -- enjoy your turkey! | ||||
| 25 | Tu 11/27 | Reinforcement learning | Ch. 21.1-21.3 | Tournament dry run #1; EC HW topics due; HW6(W) out |
Slides | 26 | Th 11/29 |
Reinforcement learning #2? | (Slides: see 11/27) |
| 27 | Tu 12/4 | Probabilistic planning | Ch. 15.1-15.2, 16.1-16.3, 17.1-17.3 | Slides
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| 28 | Th 12/6 | EC HW presentations | HW6 due; Tournament dry run #2 |
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| 29 | Tu 12/11 | Tournament | Tournament | ||
| -- | Th 12/13 | FINAL EXAM (1:00-3:00) Exam will take place in ITE 227 (our normal classroom) |
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| -- | Mo 12/17 | Project and final report due (date likely to change) |
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