Introduction slides: ppt, pdf.
Brief article on AI.
Winograd schema example on Google Translate.
|1/15 - 1/24; also returned to this (for linear programming) on 2/7.||Search. Constraint satisfaction and optimization.||Chapters 3, 4, 6. |
Homework 1, which uses the helper code from homework1_helpercode.zip.
Search slides: ppt, pdf.
More search slides: ppt, pdf
If you would like to learn more about linear and integer programming, you can go to the website of a course I taught recently; especially the introduction and branch and bound lecture notes might be useful.
|1/29, 1/31||Game playing.||Chapter 5.
Slides: ppt, pdf.
Homework 2, homework 2 files.
|1/31 - 2/21||Logic.||Chapters 7, 8,
Propositional logic: ppt, pdf.
First-order logic: ppt, pdf.
A page about the "Which horse do you want to / wanna win?" point.
|2/26, 2/28 ?||Planning.||Chapter 10. See
version of the chapter for partial-order planning (11.3).
Planning slides: ppt, pdf.
Homework 4, which uses the helper code from hw4_helper_code.zip.
|3/5 - 4/4||Probabilistic reasoning.||Chapters 13-15.
Probability slides: ppt, pdf.
Bayes nets slides: ppt, pdf.
Markov processes and HMMs slides: ppt, pdf.
Homework 5, which uses the helper code from hw5_helper_code.zip.
|4/4 - 4/18||Decision theory. Markov decision processes, POMDPs. Game theory.||Chapters 16, 17.
Decision theory slides: ppt, pdf.
MDP/POMDP slides: ppt, pdf.
Game theory slides: ppt, pdf.
|4/23||Machine learning (briefly). Determining objective functions (bonus topic).||Chapter 18 and some of the subsequent chapters if you're interested.
(You do not need
to know this in great detail since we spent so little time on this in
class, these readings are just in case you're interested.)
Machine learning slides: ppt, pdf.
Optional (not covered in class): Determining objectives slides: pptx, pdf. See also paper here.
|5/4, 2pm||Final exam.|