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 9/3 | Agents/Lisp | Ch. 2; Lisp Ch. 2-3; Graham article | Survey due | Slides |
| 3 | Th 9/5 | Problem solving as search; Lisp | Ch. 3.1-3.3; Lisp Ch. 4-5, App. A | Slides | |
| 4 | Tu 9/10 | Uninformed search | Ch. 3.4 | Slides
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| 5 | Th 9/12 | Informed search | Ch. 3.5-3.7, Lisp Ch. 7 | HW1 due; HW2(PW) out |
Slides |
| 6 | Tu 9/17 | Local search, genetic algorithms | Ch. 4.1-4.2 |
Slides
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| 7 | Th 9/19 | Constraint satisfaction | Ch. 6; Vipin Kumar, "Algorithms for Constraint Satisfaction Problems: A Survey" | Slides | |
| 8 | Tu 9/24 | Game playing | Ch. 5 | Slides
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| 9 | Th 9/26 | Game theory | Slides | ||
| 10 | Tu 10/1 | Knowledge-based agents; start propositional logic | Ch. 7.1-7.3 | Slides | |
| 11 | Th 10/3 | Propositional logic | Ch. 7.4-7.8, 8 | Slides | |
| 13 | Tu 10/08 | First-order logic, Logical inference | | HW2 Due; |
HW3 out, Project out, Project teams formed FOL,Inference
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| 14 | Th 10/10 | Logical inference, continued; knowledge representation | Ch. 12.1-12.2, 12.5-12.6 | Slides | |
| 15 | Tu 10/15 | Philosophy and history of AI |
Turing article Searle article Summary of Kurzweil's book Kevin Kelly's critique |
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| 16 | Th 10/17 | Midterm Review Day | Extra credit HW3 due; | ||
| 17 | Tu 10/22 | MIDTERM (covers material through class #14) |
Full credit homework 3 due, Project
Description, Homework 4 Out |
19 | Th 10/24 | Midterm Post-Mortem |
| 20 | Tu 10/29 | Planning | Ch. 13 | Slides | |
| 21 | Th 10/29 | Partial-order planning and Probabilistic reasoning | Project design due, HW 4 Due | Slides | 22 | Th 11/5 | Lost to Max having the plague |
| 23 | Tu 11/12 | Bayes Nets | Ch. 14.1-14.4 | HW5 out | Slides |
| 24 | Th 11/14 | Machine Learning I: Decision Trees | Ch. 18.1-18.4 | Slides | |
| 25 | Tu 11/19 | Machine learning II: K-nearest neighbor, naive Bayes, learning Bayes nets | Ch. 20.1-20.2 | Slides
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| 25 | Th 11/21 | Reinforcement learning | Ch. 21.1-21.3 | Slides | 26 | Th 11/26 |
Reinforcement learning #2? | HW5 Due,HW6 OutProject Interface | (Slides: see 11/27) |
| 27 | Tu 12/3 | Probabilistic planning | Ch. 15.1-15.2, 16.1-16.3, 17.1-17.3 | Slides
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| 28 | Th 12/5 | TBA | |||
| 30 | Tu. 12/3 | TBA | |||
| 31 | Th. 12/5 | TBA | |||
| 32 | Tu 12/10 | Review | HW 6 Due | ||
| -- | Th 12/19 | FINAL EXAM (1:00-3:00) Exam will take place in ITE 227 (our normal classroom) |
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| -- | Mo 12/19 | Project and final report due (date likely to change) |