The course material will be covered primarily in lectures and tutorials. Some examples will be done in class only, and will not appear in these notes. It is your responsibility to take notes in class to augment these slides with the extra pertinent information presented during class.
The recommended text book also contains material that will help clarify the topics covered in the lectures.
Topic | Readings Russell and Norvig (R&N) |
Slides | Notes |
---|---|---|---|
Term Specific Information Introduction What is AI? |
Introduction (1pp) Introduction (4pp) |
Sheila McIlraith weighs in on Watson's handling of the Toronto question. | |
Uninformed, Local and Heuristic Search |
Chapter 3 in https://artint.info/
Also Chapter 3 in R&N (note some of the language in the book differs from lectures but content is the same)
|
Uninformed Search (1pp) (Annotated)
Heuristic Search (1pp) (Annotated) |
A more detailed analysis of the state space of sliding tile puzzles can be found here. |
Backtracking Search (CSPs) |
Chapter 6.1, 6.2, 6.3 Chapter 4 in https://artint.info/ |
Constraint Satisfaction Search, part 1 (1pp) (Annotated)
Constraint Satisfaction Search, part 2 (1pp) (Annotated) Constraint Satisfaction Search, part 3 (1pp) (Annotated)
|
Andrew Moore's CSP animations
Alan Mackworth's lecture on GAC. Mackworth analyzes complexity of GAC (at 19:00), for those who are interested. |
Game Tree Search |
Chapter 5.1, 5.2, 5.3 (R&N,3rd ed) Chapter 5.7 also makes for interesting reading. Chapter 11 in https://artint.info/ |
Game Tree Search (1pp) (Annotated)
|
Alpha-Beta problem (done during lecture) Excellent Alpha-Beta Tutorial, thanks to Peter Abbeel |
Representing and Reasoning under Uncertainty |
Chapter 13 and 14.
Chapter 8 in https://artint.info/ |
Probability Review (1pp) (abbreviated and annotated version at this link)
Bayesian Networks (1pp) (Click here for fully annotated slides)
|
A couple of probability review problems.
VE and D-Separation problems
Slides that discuss additional topics (NOT covered on quizzes or assignments):
|
Knowledge Representation |
Chapter 7-9 and 12 (R&N 3rd ed) Chapter 7-10 (R&N 2nd ed) Chapter 13 and 14 in https://artint.info/ |
KR - Part 1 KR - Part 1 (Annotated, updated Aug 11)
KR - Part 2 |
Gordon Novak has some good KR Problem Sets on his web page:
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