Class |
Date |
Topic |
Reading |
Homework |
Comments |
| 1 | W 8/28 | Introduction | Ch. 1, Lisp Ch. 1, McCarthy paper | HW1(PW) out | Slides |
| 2 | W 9/4 | Agents/Lisp | Ch. 2, Lisp Ch. 2-3, Graham
article
Useful website: http://www.apl.jhu.edu/~hall/lisp.html |
Slides
Lisp example |
|
| 3 | M 9/9 | Problem solving as search; Lisp | Ch. 3.1-3.3, Lisp Ch. 4-5, App. A | Slides (class #3-4) | |
| 4 | W 9/11 | Uninformed search | Ch. 3.4-3.6, 3.8 | HW1 due; HW2(PW) out | (see above) |
| 5 | M 9/16 | Informed search | Ch. 4.1-4.2 (except material on constraints), Lisp Ch. 7 | Slides (class #5-6)
Key example: 8-puzzle (V0, V1, 3puzzle "polished", 8puzzle "polished") |
|
| 6 | W 9/18 | Constraint satisfaction | Ch. 3.7, 4.2 end, 4.3-4.5 | Student evaluation #1 | (see above); Slides (class #6)
Key example: map coloring |
| 7 | M 9/23 | Game playing | Ch. 5.1-5.4 | Slides (class #7-8) | |
| 8 | W 9/25 | Game playing II | Ch. 5.5-5.8 | HW2 due; HW3(P) out | (see above)
Key example: Tic-tac-toe |
| 9 | M 9/30 | Knowledge representation | Ch. 6.1-6.3 | Slides | |
| 10 | W 10/2 | Propositional logic | Ch. 6.4-6.6 | Slides (class #10/12) | |
| 11 | M 10/7 | MIDTERM #1 | |||
| 12 | W 10/9 | First-order logic | Ch. 7.1, 7.3, 7.5 | (see above); Slides (class #12/14)
Class videotape? |
|
| 13 | M 10/14 | Philosophy and history of AI | Chronology of AI; Ch. 27, Turing article; Searle article | Slides
Key example: Wumpus world reflex agent |
|
| 14 | W 10/16 | Reasoning about change and action | Ch. 7.6-7.10 | HW3 due; HW4(W) out | (see above)
Dr. desJardins away; guest lecturer Yun Peng; class feedback session |
| 15 | M 10/21 | Logical inference | Ch. 9.1-9.4 | Slides (class #15/16)
Gremlin example |
|
| 16 | W 10/23 | Resolution | Ch. 9.5-9.6 | (see above) | |
| 17 | M 10/28 | Knowledge representation: Frame systems, uncertainty | Ch. 10.5-10.6, 14.1, 14.2 (skim), 15.6 | Project proposal due | Slides
Dr. desJardins away; guest lecturer Scott Cost |
| 18 | W 10/30 | Probabilistic reasoning | Ch. 14.2-14.6 | HW4 due | Slides
Dr. desJardins away; guest lecturer Lise Getoor (UMd) |
| 19 | M 11/4 | Bayesian networks | Ch. 15.1-15.2 | Slides | |
| 20 | W 11/6 | Forward-chaining planning | Ch. 11.1-11.4 | HW5 out | Slides (class #20/21/23)
Key example: Alarm |
| 21 | M 11/11 | STRIPS planning | Reading TBA | (see above) | |
| 22 | W 11/13 | MIDTERM #2 | Dr. desJardins away; guest proctor Tim Finin | ||
| 23 | M 11/18 | Partial-order planning | Ch. 11.4-11.7 | Project design due; individual reports due | (see above)
Key example: Blocks world |
| 24 | W 11/20 | Hierarchical planning | Ch. 12 | HW5 due; HW6(W) out | Slides (class #24) |
| 25 | M 11/25 | Machine learning I: Decision trees | Ch. 18.1-18.4 | Slides (class #25-26) | |
| 26 | W 11/27 | Machine learning II: Version spaces, COLT | Ch. 18.5-18.7 | (see above)
Key example: Weather |
|
| 27 | M 12/2 | Neural networks | Ch. 19.1-19.3 | Slides (class #27-28) | |
| 28 | W 12/4 | Knowledge-based learning | Ch. 21.1-21.4 | (Tournament dry run)
Draft final report due; HW6 due |
|
| 29 | M 12/9 | Tournament | Tournament | ||
| M 12/16 | PROJECT AND FINAL REPORT DUE | ||||
| -- | W 12/18 | FINAL EXAM, 1-3 p.m. |