University of Waterloo
Term and Year of Offering: Winter 2014
Course Number and Title: CS486/686, Introduction to
Artificial Intelligence
Website:
cs.uwaterloo.ca/~ppoupart/teaching/cs486-winter14/cs486-winter14.html
Instructor's Name |
Office Location |
Contact |
Office Hours |
Pascal Poupart |
DC2514 |
ppoupart@uwaterloo.ca |
Wed 11:30-13:00 |
TA's Name |
Office Location |
Contact |
Office Hours |
Abdullah Rashwan
|
|
arashwan@uwaterloo.ca |
|
Daniel Recoskie
|
|
dprecosk@uwaterloo.ca
|
|
Course Description:
The design of automated systems capable of accomplishing complicated
tasks is at the heart of computer science. Abstractly, automated
systems can be viewed as taking inputs and producing outputs towards
the realization of some objectives. In practice, the design of
systems that produce the best possible outputs can be quite
challenging when the choice of outputs is constrained, the
consequences of the outputs are uncertain and/or dependent on other
systems, the information provided by the inputs is incomplete and/or
noisy, there are multiple (possibly competing) objectives to
satisfy, the system must adapt to its environment over time, etc.
This course provides an introduction to Artificial Intelligence,
covering some of the core topics that underlay automated reasoning.
The modeling techniques that will be covered are quite versatile and
can be used to tackle a wide range of problems in many fields
including natural language processing (e.g., topic modeling,
document clustering), robotics (e.g., mobile robot navigation),
automated diagnosis (e.g., medical diagnosis, fault detection), data
mining (e.g., fraud detection, information retrieval), operations
research (e.g., resource allocation, maintenance scheduling),
assistive technologies, etc.
Course Objectives:
To give an introduction to the fundamental problems of artificial
intelligence and an introduction to the basic models and algorithms
used in tackling these problems. Another objective is to expose the
student to frontier areas of computer science, while providing
sufficient foundations to enable further study.
Course Overview:
The topics we will cover include:
- Introduction to Artificial Intelligence
- Search and Problem Solving
- Uninformed Search
- Informed Search
- Constraint Satisfaction Problems
- Local search
- Reasoning Under Uncertainty
- Probability Theory
- Bayesian Networks
- Utility Theory
- Decision Networks
- Markov Decision Processes
- Machine Learning
- Inductive Learning
- Decision Trees
- Statistical Learning
- Ensemble Learning
- Bandits
- Reinforcement Learning
- Other areas of Artificial Intelligence
- Natural Language Processing
- Assistive Technologies
Required text:
The textbook for CS486/686 is Artificial
Intelligence: A Modern Approach (3rd Edition), Prentice
Hall, by Russell and Norvig. This
will be the main reference for the course. A few copies are
currently on reserve at the library. Readings in the textbook
are assigned for every lecture in the course
schedule.
Evaluation:
The grading scheme for the course is as follows.
CS486:
- Assignments (4): 40% (10% each)
- Midterm test: 20%
- Final Exam: 40%
- Optional project: 5% bonus
CS686 (graduate students only):
- Assignments (4): 28% (7% each)
- Midterm test: 12%
- Final Exam: 35%
- Project: 25%
Assignments
There will be four assignments given the course. Each assignment
will have a theoretical part and a programming part.
Assignments are done individually (i.e., no team). You are
free to program in the language of your choice, however Python and
Matlab are recommended since they provide a convenient high-level
programming environment for matrix operations. If you decide
to program in Matlab, the IST group maintains a nice set of online references for Matlab
including a tutorial.
The approximate out and
due dates are:
- A1: out Jan 14, due Jan 29 (midnight)
- A2: out Jan 30, due Feb 24 (midnight)
- A3: out Feb 27, due Mar 17 (midnight)
- A4: out Mar 18, due Apr 2 (midnight)
Tests
There will be one midterm test of
75 minutes duration.
The midterm is scheduled on March
6th.
There will also be a final examination of 2.5 hours to be scheduled
by the registrar.
Rules for Group Work:
Assignments must be done individually. Projects can be done in
groups of up to 3 people for undergraduate students, but must be
done individually for graduate students.
Indication of how late submission of assignments and missed
assignments will be treated
On the due date of an assignment, the work done to date should be
submitted electronically on the LEARN website; further material may
be submitted for half credit within 24 hours. Assignments submitted
more than 24 hours late will not be marked.
Indication of where students are to submit assignments and pick
up marked assignments
Assignments must be submitted electronically on the LEARN website.
Marked assignments will be returned electronically via the LEARN
website.
Academic Integrity: In order to maintain a culture of
academic integrity, members of the University of Waterloo community
are expected to promote honesty, trust, fairness, respect and
responsibility. [Check www.uwaterloo.ca/academicintegrity/
for more information.]
Grievance: A student who believes that a decision
affecting some aspect of his/her university life has been unfair
or unreasonable may have grounds for initiating a grievance. Read
Policy 70, Student Petitions and Grievances, Section 4, www.adm.uwaterloo.ca/infosec/Policies/policy70.htm.
When in doubt please be certain to contact the department's
administrative assistant who will provide further assistance.
Discipline: A student is expected to know what constitutes
academic integrity [check www.uwaterloo.ca/academicintegrity/]
to avoid committing an academic offence, and to take
responsibility for his/her actions. A student who is unsure
whether an action constitutes an offence, or who needs help in
learning how to avoid offences (e.g., plagiarism, cheating) or
about 'rules' for group work/collaboration should seek guidance
from the course instructor, academic advisor, or the undergraduate
Associate Dean. For information on categories of offences and
types of penalties, students should refer to Policy 71, Student
Discipline, www.adm.uwaterloo.ca/infosec/Policies/policy71.htm.
For typical penalties check Guidelines for the Assessment of
Penalties, www.adm.uwaterloo.ca/infosec/guidelines/penaltyguidelines.htm.
Appeals: A decision made or penalty imposed under Policy
70 (Student Petitions and Grievances) (other than a petition) or
Policy 71 (Student Discipline) may be appealed if there is a
ground. A student who believes he/she has a ground for an appeal
should refer to Policy 72 (Student Appeals) www.adm.uwaterloo.ca/infosec/Policies/policy72.htm.
Note for Students with Disabilities: The Office for
persons with Disabilities (OPD), located in Needles Hall, Room
1132, collaborates with all academic departments to arrange
appropriate accommodations for students with disabilities without
compromising the academic integrity of the curriculum. If you
require academic accommodations to lessen the impact of your
disability, please register with the OPD at the beginning of each
academic term.