Course Overview
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
underly 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.
Instructor
- Kate Larson (klarson @ uwaterloo.ca)
Office Hours: Mondays 3:00-4:00pm in DC 2518
Teaching Assistants
- Arthur Carvalho (a3carval @ uwaterloo.ca)
- Hadi Hosseini (h5hossei @ uwaterloo.ca)
- Milad Khaki (mkhaki @ uwaterloo.ca)
Readings
The main text is
- Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, Prentice Hall, Third Edition, 2010.
A second useful reference is
- David Poole and Alan Mackworth, Artificial Intelligence: Foundations of Computational Agents, Cambridge University Press, 2010, Available online
Communication
We will be using
the
Piazza
discussion board. Please sign up for Piazza and the
course
here.
Public Piazza posts (can be anonymous) are the prefererd method for
questions about course material. Students can then help each other out
and instructors can also read and reply so that everyone in class can
see the responses. Private Piazza posts (to instructors only) can be
used for any post that contains solution snippets or private
questions.
Evaluation
For students registered in CS 486
- 4 Assignments: 40%
- Midterm Exam (in class on October 10): 20%
- Final Exam: 40%
- Project (Optional): Up to 5 bonus marks
For students registered in CS 686
- 4 Assignments: 28%
- Midterm (in class on October 10): 12%
- Final: 35%
- Project: 25%
Academic Integrity
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. All members of the UW community are expected to hold
to the highest standard of academic integrity in their studies,
teaching, and research. The Office of Academic Integrity's website (www.uwaterloo.ca/academicintegrity)
contains detailed information on UW policy for students and
faculty. This site explains why academic integrity is important and
how students can avoid academic misconduct. It also identifies
resources available on campus for students and faculty to help achieve
academic integrity in and out of the classroom.
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, http://www.adm.uwaterloo.ca/infosec/Policies/policy70.htm
Discipline: A student is expected to know what constitutes
academic integrity, to avoid committing academic offenses, and to take
responsibility for his/her actions. A student who is unsure whether an
action constitutes an offense, or who needs help in learning how to
avoid offenses (e.g., plagiarism, cheating) or about rules for group
work/collaboration should seek guidance from the course professor,
academic advisor, or the Undergraduate Associate Dean. When misconduct
has been found to have occurred, disciplinary penalties will be
imposed under Policy 71 Student Discipline. For information on
categories of offenses and types of penalties, students should refer
to Policy 71 - Student Discipline, http://www.adm.uwaterloo.ca/infosec/Policies/policy71.htm
Avoiding Academic Offenses: Most students are unaware of the
line between acceptable and unacceptable academic behaviour,
especially when discussing assignments with classmates and using the
work of other students. For information on commonly misunderstood
academic offenses and how to avoid them, students should refer to the
Faculty of Mathematics Cheating and Student Academic Discipline
Policy, http://www.math.uwaterloo.ca/navigation/Current/cheating_policy.shtml
Appeals: A student may appeal the finding and/or penalty in a decision
made under Policy 70 - Student Petitions and Grievances (other than
regarding a petition) or Policy 71 - Student Discipline if a ground
for an appeal can be established. Read Policy 72 - Student Appeals,
http://www.adm.uwaterloo.ca/infosec/Policies/policy72
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
accomodations for students with disabilities without compromising the
academic integrity of the curriculum. If you require accomodations to
lessen the impact of your disability, please register with the OPD at
the beginning of each academic term.