(Term 2, Session 201, 2010-11)
|Overview||Grades||Text||Schedule||Assessing your own learning|
- Meeting Times: Monday, Wednesday, Friday, 3:00 - 4:00 PM
- First Class: Wednesday, January 5, 2011
- Location: DMP 110
- Instructor: Frank Hutter
- Instructor's Office Location: ISICS X560 (beta lab)
- Instructor's Office Hours: Monday, Wednesday, Friday, 4-4:30pm in X530 (i.e., immediately after each lecture); available other times by appointment.
- Simona Radu: Monday, 10am-11am (changed from 11-12), X150 (Learning Center)
- Vasanth Rajendran: Thursday, 3pm-4pm, X150 (Learning Center)
- Mike Chiang: Wed 1pm-2pm, X150 (Learning Center)
- Course Discussion Board: (the place to submit your questions and get answers, as well as see answers given to others): log into WebCT Vista using your CWL
- AISpace: demo applets that illustrate some of the techniques covered in class
- Prerequisites: Either (a) CPSC 221 or (b) both of CPSC 216, CPSC 220 or (c) all of CPSC 211, CPSC 260, EECE 320.
- Final exam: TBA
What do I do if I get the flu?
- Self-isolate: stay away from campus until you're fever-free for 24 hours.
- Get a doctor's note if you're missing midterm or final, or if you'll be late for an assignment.
the course on this page,
Frank if you have additional questions.
Grading Scheme: Evaluation will be based on a set of assignments, a midterm, and an exam. Important: you must pass the final in order to pass the course. The instructor reserves the right to adjust this grading scheme during the term, if necessary.
- Assignments -- 20%
- Midterm -- 30%
- Final -- 50%
If your grade improves substantially from the midterm to the final, defined as a final exam grade that is at least 20% higher than the midterm grade, then the following grade breakdown will be used instead.
- Assignments -- 20%
- Midterm -- 15%
- Final -- 65%
The assignment grade will be computed by adding up the number of points you get across all assignments, dividing this number by the number of possible points, and multiplying by 20. Assignments will not be graded out of the same number of points; this means that they will not be weighted equally.
Submitting assignments via handin: Assignments are to be handed in electronically via the handin tool. The WebCT discussion board for assignment 0 has instructions for how to do this. In order to use handin, you will need to activate your CS account (every registered student already has an account, you just need to activate it). You can activate your account on the acount activation page.
Late Assignments: Assignments are to be handed in electronically via Handin by 3pm on the due date (see the point above). However, every student is allotted four "late days", which allow assignments to be handed in late without penalty on four days or parts of days during the term. The purpose of late days is to allow students the flexibility to manage unexpected obstacles to coursework that arise during the course of the term, such as travel, moderate illness, conflicts with other courses, extracurricular obligations, job interviews, etc. Thus, additional late days will NOT be granted except under truly exceptional circumstances. If an assignment is submitted late and a student has used up all of her/his late days, 20% will be deducted for every day the assignment is late. (E.g., an assignment 2 days late and graded out of 100 points will be awarded a maximum of 60 points.)
How late does something have to be to use up a late day? A day is defined as a 24-hour block of time beginning at 3 PM on the day an assignment is due. To use a late day, write the number of late days claimed on the first page of your assignment.. Examples:
- Handing in an assignment at the end of lecture on the day it is due consumes one late day.
- Handing in an assignment at 10:15 the morning after it is due consumes one late day.
- Handing in an assignment at 3:30 the day after it is due consumes two late days.
Missing Deadlines or Exams: In truly exceptional circumstances, when accompanied by a note from Student Health Services or a Department Advisor, the following arrangements will be made.
- If an assignment cannot be completed, the assignment grade will be computed based on the remaining assignments. Note that such an arrangement is extremely unusual--the late day system is intended to allow students to accommodate disruptions from moderate illness without contacting the instructor.
- If the midterm is missed, its grades will be shifted to the final. This means the final will count for 80% of the final grade, and assignments will count for the remaining 20%.
- If the final is missed, a make-up final will be scheduled. This make-up final will be held as soon as possible after the regularly scheduled final.
Academic Conduct: Submitting the work of another person as your own (i.e. plagiarism) constitutes academic misconduct, as does communication with others (either as donor or recipient) in ways other than those permitted for homework and exams. Such actions will not be tolerated. Specifically, for this course, the rules are as follows:
- For assignments 1-4 (not for assignment 0), you may work with one other student. That student must also be a CPSC 322 student this term, and you will both have to officially declare that you collaborated when submitting your assignment. Both of you will have to submit your assignments separately.
- You cannot work with or copy work from anyone else. You may not, under any circumstances, submit any solution not written by yourself, look at a student's solution who is not your official partner (this includes the solutions from assignments completed in the past), or previous sample solutions, and you may not share your own work with others. All work for this course is required to be new work and cannot be submitted as part of an assignment in another course without the approval of all instructors involved.
- You may, however, discuss your solutions and design decisions with your fellow students on a high level. In other words, you can talk about the assignments, but you cannot look at or copy other people's answers.
Violations of these rules constitute very serious academic misconduct, and they are subject to penalties ranging from a grade of zero on the current and *all* the previous assignments to indefinite suspension from the University. More information on procedures and penalties can be found in the Department's Policy on Plagiarism and collaboration and in UBC regulations on student discipline . If you are in any doubt about the interpretation of any of these rules, consult the instructor or a TA!
You can find the
course schedule and lecture slides
below. The schedule is tentative and will change throughout the term.
Future assignment due dates are
provided to give you a rough sense; however, they are also subject to
change. I will try to post the slides for each lecture by 2am the day
of the lecture; this allows you to print them when you get up in the
morning. I don't promise to use exactly that version in class, but it
should be very close. If I do further changes, I will post the final
version after class, at the latest when I post the slides for the next
If you are curious what's coming up in future lectures, here are Cristina Conati's slides from last term; the content should be quite similar to this year but the form differs a lot (so these are NOT useful for note taking in class).
|(1) Wed, Jan 5||Intro 1: What is AI? [ppt] [pdf]||1.1-1.3
||Assignment 0 out|
|(2) Fri, Jan 7||Intro 2: Representational Dimensions [ppt] [pdf]||1.4-1.5|
|(3) Mon, Jan 10||Intro 3: Applications of AI [ppt] [pdf]||1.6
|(4) Wed, Jan 12||Search 1: Representation & Search Framework [ppt] [pdf]||3.0-3.4
||Assignment 0 due|
|(5) Fri, Jan 14||Search 2: BFS and DFS [ppt] [pdf]||3.5||Exercise 1 , solutions|
|(6) Mon, Jan 17||Search 3: Search with Costs & Heuristic Search [ppt] [pdf]||3.5.3,
|(7) Wed, Jan 19||Search 4: Heuristic Search: A* [ppt] [pdf]||3.6||Exercise 2
|(8) Fri, Jan 21||Search 5: A* optimality, cycle checking [ppt] [pdf]||3.6
|(9) Mon, Jan 24||Search 6: Iterative Deepening (IDS) [draft:ppt pdf] [covered: ppt pdf]||3.7.3||Assignment 1 out|
|(10) Wed, Jan 26||Search 7: Multiple Path Pruning, IDS [draft:ppt pdf] [covered: ppt pdf]||3.7.1-3.7.3|
|(11) Fri, Jan 28||CSP 1: Branch & Bound. CSP: Intro [ppt] [pdf]||3.7 & 4.0-4.2||Exercise 3 , solutions|
|(12) Mon, Jan 31||CSP 2: Solving CSP using search [ppt] [pdf]||4.3-4.4|
|(13) Wed, Feb 2||CSP 3: Arc consistency [ppt] [pdf]||4.5
4 , solutions
|(14) Fri, Feb 4||CSP 4: Domain splitting [draft: ppt pdf] [covered: ppt pdf]||4.6||Sudoku programming question out|
5 , solutions
Assignment 1 due
Assignment 2 out
|(16) Wed, Feb 9||CSP 6: Stochastic local search [ppt] [pdf]||4.8|
7: Stochastic local
search algorithms [ppt]
Watson in the news: NYTimes,
More technical: AI magazine article: Building Watson
Watch: video of practice round
|Mon, Feb 14||Reading break; university closed|
|Wed, Feb 16||Reading break; university closed|
|Fri, Feb 18||Reading break; university closed|
|(18) Mon, Feb 21||Planning 1: Representation and Forward Planning [ppt] [pdf]||8.0, 8.1, 8,2||Exercise 6 , solutions|
|(19) Wed, Feb 23||Planning 2: Forward Planning and CSP Planning [ppt] [pdf]||8.2,
||Assignment 2 due|
|Fri, Feb 25||Midterm review (all whiteboard, no slides)|
|Mon, Feb 28||Midterm (3pm-4:30pm in FSC 1005)||Exercise 7 , solutions|
|(20) Wed, Mar 2||Planning 3: CSP Planning wrap up. [ppt] [pdf]||8.4||Assignment 3 out|
|(21) Fri, Mar 4||Logic 1: Intro & Propositional Definite Clause Logic [ppt] [pdf]||5.1-5.2
||Exercise 8 , solutions|
|(22) Mon, Mar 7||Logic 2: Proof procedures, soundness and correctness [ppt] [pdf]||5.2|
|(23) Wed, Mar 9||Logic 3: Bottom-up Proof Procedure [ppt] [pdf]||5.2||Exercise 9 , solutions|
|(24) Fri, Mar 11||Logic 4: Top-Down Procedure and Datalog [ppt] [pdf]||5.2|
|(25) Mon, Mar 14||Logic 5: wrap-up [ppt] [pdf] & presentation: SLS for UBC exam scheduling||12.3|
1: Probability Theory [ppt]
10 , solutions
Assignment 3 due
|(27) Fri, Mar 18||Uncertainty 2: Conditional Probability, Bayes Rule, Chain Rule [ppt] [pdf]||6.1.3||Assignment 4 out|
|(28) Mon, Mar 21||Uncertainty 3: Independence [ppt] [pdf]||6.2|
|(29) Wed, Mar 23||Uncertainty 4: Bayesian networks intro [ppt] [pdf]||6.3 - 6.3.1|
|(30) Fri, Mar 25||Uncertainty 5: Independence and Inference [ppt] [pdf]||6.3.1|
|(31) Mon, Mar 28||Uncertainty 6: Variable Elimination [ppt] [pdf]||6.4.1||Exercise 11 , solutions|
||Decision Theory 1: Uncertainty wrap-up. Single Decisions [ppt] [pdf]||6.4.1 & 9.2||newspaper.xml|
|(33) Fri, Apr 1||Decision Theory 2: Single and sequential decisions. VE. [ppt] [pdf]||9.2-9.3||
12 , solutions bikeride_tires_flat_tools.xml
|(34) Mon, Apr 4||Decision Theory 3: optimal policies for sequential decisions [ppt] [pdf]||9.3||Assignment 4 due|
|(35) Wed, Apr 6||Perspectives and Final Review [ppt] [pdf]||Exercise 13 , solutions wii.xml|
|Mon, Apr 11||Final exam, 3:30 pm DMP 310. This is on the first day of exams.|
- We created a list of "learning goals" for the course, which detail concrete skills you should have after mastering each of the units. The list can be accessed via WebCT Vista.
Exercises are ungraded practice problems to help you prepare for assignments and exams. They're optional, but will definitely help you to master the course material. All exercises will be put up via WebCT Vista.