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Overview
Course Description: This course provides
an introduction to the field of artificial
intelligence. The major topics covered will include
reasoning and representation, search, constraint
satisfaction problems, planning, logic, reasoning under
uncertainty, and planning under uncertainty.
- Meeting Times: Monday, Wednesday, Friday, 3:00
- 3:50 pm
- First Class: Wednesday, January 2, 2013
- Location: DMP 110
- Instructor: Alan K. Mackworth
- Instructor's Office Location: ICCS 121
- Instructor's Office Hours: Monday 4-4:30 pm,
Wednesday 4-4:30pm or by appointment
- TAs: (TA Office Hours are in the Demco
Learning Centre, ICCS 150)
- Shafiq
Joty (Office Hour: Monday 1:00 pm)
- Mehran Kazemi smkazemi@cs.ubc.ca (Office
Hour: Wednesday 11:00 am)
- Pooyan
Fazli (Office Hour: Friday 12:00 noon)
- Course Discussion Board: (the place to submit
your questions and get answers, as well as see answers
given to others): log into Connect
using your CWL. If you need assistance with Connect,
there are number of resources available. You can access
those resources at http://elearning.ubc.ca/connect/student-resources/.
If you have technical issues with Connect should contact
the IT Service Centre Help Desk at 604.822.2008 or http://it.ubc.ca/contact/helpdesk.html.
- AIspace: demo applets
that illustrate most 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.
- Follow the course on this page, and
contact Alan if you have additional questions.
Grades
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 and
hardcopy: Assignments
are to be handed in electronically via the handin tool and
in hardcopy. 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 account
activation page. A printout of your assignment
must also be submitted to the assignment box #4 located in
room X235 on the 2nd floor of the X-wing of ICCS.
Late Assignments: Assignments
are to be handed in electronically via handin
and in hardcopy by 1 pm on the due date. If the
assignment is late, get the hardcopy date stamped in the CS
office, ICCS 201. 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
1:00 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 4 pm on the day it is due
consumes one late day.
- Handing in an assignment at 10:15 am the morning after
it is due consumes one late day.
- Handing in an assignment at 1:30 pm 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, 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!
Text
We will be using the text Artificial Intelligence:
Foundations of Computational Agents by
David L. Poole and Alan K. Mackworth. The entire
book is available (for free, as in beer!) in e-format at
the above link. Copies are available in the UBC Bookstore
and a copy is on reserve in the CS
reading
room. Although this text will be our main reference
for the class, it must be stressed that you will need to
know all the material covered in class, whether or not it
is included in the readings or available on-line.
Likewise, you are responsible for all the material in
assigned readings, whether or not it is covered in class.
If you'd like to refer to an alternate text, I recommend Russell and Norvig's
Artificial Intelligence: A Modern Approach (Third
edition). I've arranged for a copy to be put
on reserve in the CS
reading
room.
Schedule
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 11pm the day before 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 lecture.
Date |
Lecture |
Book Sections
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Notes
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(1)
Wed, Jan 2 |
Intro
1: What is AI?
(.pdf) |
1.1-1.3
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Assignment
0 out |
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(2) Fri, Jan 4 |
Intro 2:
Representational Dimensions (.pdf) |
1.4-1.5 |
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(3) Mon, Jan 7 |
Intro
3: Applications of AI (.pdf) |
1.6
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(4) Wed, Jan 9
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Search
1:
Representation & Search Framework (.pdf) |
3.0-3.4
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(5) Fri, Jan 11 |
Search 2:
BFS and DFS
(.pdf) |
3.5 |
Assignment 0 due
Exercise
1, Solutions
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(6) Mon, Jan 14 |
Search
3:
Search
with
Costs & Heuristic Search
(.pdf) |
3.5.3, 3.6.1
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(7) Wed, Jan 16 |
Search
4: Heuristic Search: A*
(.pdf) |
3.6 |
Exercise 2,
Solutions |
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(8) Fri, Jan 18
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Search 5: A*
optimality, cycle checking
(.pdf) |
3.6
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(9) Mon, Jan 21
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Search
6:
Iterative
Deepening
(IDS)
and
IDA* (.pdf) |
3.7.3 |
Assignment
1 out
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(10) Wed, Jan 23 |
Search
7:
Multiple
Path Pruning, IDS
and IDA*
(.pdf) |
3.7.1-3.7.3 |
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(11) Fri, Jan 25
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CSP
1: Branch
& Bound. CSP: Intro (.pdf) |
3.7 & 4.0-4.2 |
Exercise 3, Solutions |
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(12) Mon, Jan 28
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CSP
2: Solving
CSP using search (.pdf) |
4.3-4.4 |
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(13)
Wed, Jan 30
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CSP 3:
Arc consistency (.pdf) |
4.5
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Exercise 4, Solutions
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(14) Fri, Feb 1
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CSP 4:
Domain splitting (.pdf)
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4.6
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Assignment 1 due
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(15)
Mon, Feb 4
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CSP 5:
Local search (.pdf) |
4.8
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Assignment 2 out
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(16) Wed,
Feb 6
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CSP 6:
Stochastic local search (.pdf) |
4.8 |
Exercise 5,
Solutions
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(17) Fri,
Feb 8
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CSP 7:
Stochastic local search algorithms (.pdf) |
4.8 |
roundabouts.xml |
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Mon,
Feb 11 |
UBC closed
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(18) Wed, Feb 13 |
Planning
1: Representation and Forward Planning (.pdf) |
8.0, 8.1, 8,2 |
Exercise 6, Solutions
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(19)
Fri, Feb 15 |
Planning
2: Forward
Planning
and
CSP
Planning (.pdf) |
8.2, 8.4 |
Assignment
2
due, Assignment 3 out Exercise
7, Solutions |
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Feb 18-22
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UBC Midterm
break
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(20) Mon, Feb
25
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Planning 3:
CSP Planning wrap up. (.pdf) |
8.4 |
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(21)
Wed, Feb 27 |
Logic
1:
Intro
&
Propositional Definite Clause Logic
(.pdf) |
5.1-5.2 |
Exercise
8,
Solutions |
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(22)
Fri, Mar 1 |
Logic
2: Proof procedures, soundness and
completeness
(.pdf) |
5.2 |
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(23) Mon, Mar 4
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Logic
3:
Bottom-up and
Top-down Proof Procedures
(.pdf)
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5.2
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Exercise 9,
Solutions
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Wed, Mar 6
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Midterm exam
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(24) Fri, Mar 8 |
Logic
4:
Top-Down Procedure,
Datalog and Big Picture (.pdf) |
5.2, 12.3
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(25) Mon, Mar 11 |
Uncertainty 1:
Probability Theory: Intro (.pdf)
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6.1, 6.1.1,6.1.3 |
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(26) Wed, Mar 13 |
Uncertainty
2:
Conditional
Probability,
Bayes Rule, Chain Rule (.pdf) |
6.1.3 |
Assignment
3 due |
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(27) Fri, Mar 15 |
Uncertainty
3: Independence (.pdf) |
6.2 |
Assignment 4 out |
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(28) Mon, Mar 18
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Uncertainty 4:
Bayesian networks intro (.pdf) |
6.3 - 6.3.1 |
Exercise 10
Solutions
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(29) Wed, Mar 20 |
Uncertainty 5:
Independence and Inference (.pdf) |
6.3.1 |
credit_card_fraud.xml
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(30) Fri,
Mar 22 |
Uncertainty
6: Variable Elimination (.pdf) |
6.4.1 |
Exercise 11
Solutions |
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(31) Mon, Mar 25
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Decision
Theory 1: Uncertainty wrap-up. Single
Decisions (.pdf) |
6.4.1 & 9.2 |
newspaper.xml |
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(32) Wed, Mar 27
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Decision
Theory 2: Single and sequential
decisions (.pdf) |
9.2-9.3 |
Exercise
12 Solutions
bikeride_tires_flat_tools.xml |
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Fri, Mar 29
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UBC closed
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Mon, Apr 1
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UBC closed
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(33) Wed, Apr 3 |
Decision
Theory
3:
Optimal policies for sequential
decisions (.pdf) |
9.3 |
Assignment
4 due
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(34) Fri, Apr 5 |
Perspectives
and Final Review
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Exercise
13 Solutions
wii.xml
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Thu, Apr 18
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Final exam
in PHRM 1101, 8:30 am - 11:00 am |
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Assessing
Your
Own Learning
- We have created a list of learning goals for
the course, which detail concrete skills
you should have after mastering each of the units. The
list is available via Connect.
-
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 the exercises will be put up here, with
solutions, on the schedule.
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