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Instructor and TA
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Instructor: Kate Larson (kate.larson@uwaterloo.ca) Office hours:
TAs:
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LEARN Technical Support
LEARN Help support is available Monday to Friday, 8:30 AM to 4:30 PM (Eastern Time). |
Include your full name, WatIAM user ID, student number, and course name and number. |
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Student Resources
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This syllabus is a guideline for the course and not a contract. As such, its terms may be altered when doing so is, in the opinion of the instructor(s), in the best interests of the class.
Calendar Description: Goals and methods of artificial intelligence. Methods of general problem solving. Knowledge representation and reasoning. Planning. Reasoning about uncertainty. Machine learning. Multi-agent systems.
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), machine learning (e.g., speech recognition, computer vision), operations research (e.g., resource allocation, maintenance scheduling), assistive technologies, etc.
Introduction to Artificial Intelligence
Search and Problem Solving
Reasoning under uncertainty
Machine learning
Decision making
Multi-agent systems
Prereqs: CS 341
Coreq: STAT 206 or 231 or 241
| Assessments |
CS 486 Weight (%) |
CS 686 Weight (%) |
|---|---|---|
| Assignments (4) | 40 | 28 |
| Midterm Exam | 20 | 12 |
| Final Exam | 40 | 35 |
| Project Proposal | NA | 0 |
| Project | NA | 25 |
The four assignments contain both written and programming exercises and cover the new material in the course since the previous assignment.
Please start working on the assignments in advance of the deadlines. Late submissions for assignments will be accepted only up to 48 hours after the original due date. There is no penalty for accepted late submissions. Assignments can be submitted multiple times, and the last one will be used for marking. Course personnel will not normally give assistance for assignments after their original due dates.
The 48-hour grace period does not apply to the CS 686 proposal and project; no late submissions will be accepted for them unless clearly specified on the project information page.
You must notify your instructor(s) well before the due date of any severe, long-lasting problems that prevent you from completing an assignment on time.
The recent advances in generative AI (eg ChatGPT, Stable Diffusion, DAll-E, CoPilot, Llama, etc) are exciting and have opened up many exciting avenues for AI applications and research. While we will discuss generative AI, we will not be solely focussing on it since the field of artificial intelligence is significantly broader than large language models (LLMs) or VLMs.
While we encourage you to explore and experiment with generative AI, these models are not to be used in assignments unless the assignment clearly states that they are allowed. If the use of generative AI is allowed on an assignment (or part of an assignment) then proper documentation, citation, and acknowledgement is required.
Recommendations for how to cite generative AI in student work at the University of Waterloo may be found through the Library: https://subjectguides.uwaterloo.ca/chatgpt_generative_ai. Please be aware that generative AI is known to falsify references to other work and may fabricate facts and inaccurately express ideas. GenAI generates content based on the input of other human authors and may therefore contain inaccuracies or reflect biases.
In addition, you should be aware that the legal/copyright status of generative AI inputs and outputs is unclear. Exercise caution when using large portions of content from AI sources, especially images. More information is available from the Copyright Advisory Committee: https://uwaterloo.ca/copyright-at-waterloo/teaching/generative-artificial-intelligence
You are accountable for the content and accuracy of all work you submit in this class, including any supported by generative AI.
The midterm exam is scheduled to be held on Monday, October 16, 2023 from 19:00-20:50. The room UW AL 116 is currently booked for the midterm exam.
The final exam is written-only (no programming) but covers material from the whole term. You will have 2 hours and 30 minutes to complete the set of questions.
If your score in the final exam is below 50%, you cannot pass the course.
The final exam will be administered on campus in accordance with University policies. The exact date and time of the final exam is yet to be scheduled by the Registrar office, we will update the syllabus once we receive more details.
We will be using Learn and Piazza in this course. We will post lecture material, assignments, and general course information on Learn. We will use Piazza as our discussion forum where people can ask and answer questions about the course material.
Piazza link: https://piazza.com/uwaterloo.ca/fall2023/cs486686
The instructor will hold both in-person and online office hours (see times listed above). We will use Teams for the online office hours. Every student enrolled in the course should be automatically added to the CS 486/686 - Fall 2023 Team. At the start of each online office hour I will start a conversation. To indicate that you would like some help, please respond to the conversation and I will initiate a video call with you.
Unfortunately, Covid-19 is still with us. If the university is required to close, we will follow the University of Waterloo and the Faculty of Mathematics guidelines for moving the course online. Note that this might require moving the final exam online. If this decision is made by the university then all students will be informed immediately.
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 the Office of Academic Integrity for more information.]
Grievance: A student who believes that a decision affecting some aspect of their university life has been unfair or unreasonable may have grounds for initiating a grievance. Read Policy 70, Student Petitions and Grievances, Section 4. 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 to avoid committing an academic offence, and to take responsibility for their actions. [Check the Office of Academic Integrity for more information.] 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. For typical penalties, check Guidelines for the Assessment of Penalties.
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 they have a ground for an appeal should refer to Policy 72, Student Appeals.
Turnitin.com: Text matching software (Turnitin®) may be used to screen assignments in this course. Turnitin® is used to verify that all materials and sources in assignments are documented. Students' submissions are stored on a U.S. server, therefore students must be given an alternative (e.g., scaffolded assignment or annotated bibliography), if they are concerned about their privacy and/or security. Students will be given due notice, in the first week of the term and/or at the time assignment details are provided, about arrangements and alternatives for the use of Turnitin in this course.
It is the responsibility of the student to notify the instructor if they, in the first week of term or at the time assignment details are provided, wish to submit the alternate assignment.
It is our intent that students from all diverse backgrounds and perspectives be well served by this course, and that students’ learning needs be addressed both in and out of class. We recognize the immense value of the diversity in identities, perspectives, and contributions that students bring, and the benefit it has on our educational environment. Your suggestions are encouraged and appreciated. Please let us know ways to improve the effectiveness of the course for you personally or for other students or student groups. In particular:
AccessAbility Services, located in Needles Hall North, Room 1401, 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 AccessAbility at the beginning of each academic term.
The Faculty of Math encourages students to seek out mental health support if needed.
On-campus Resources:
Off-campus Resources:
We acknowledge that we live and work on the traditional territory of the Attawandaron (Neutral), Anishinaabeg, and Haudenosaunee peoples. The University of Waterloo is situated on the Haldimand Tract, the land promised to the Six Nations that includes ten kilometres on each side of the Grand River.