Simon Fraser University
Engaging the World

Course Outlines

Spring 2025 - IAT 813 G100

Artificial Intelligence in Computational Art and Design (3)

Class Number: 5798

Delivery Method: In Person

Overview

  • Course Times + Location:

    Jan 6 – Apr 9, 2025: Thu, 9:30 a.m.–12:20 p.m.
    Surrey

Description

CALENDAR DESCRIPTION:

Applications of computational intelligence to art and design are introduced through a set of motivating examples. Specific areas of application include knowledge representation, problem solving, rule based systems, ontologies and statistical reasoning.

COURSE DETAILS:


This course is fundamental for anyone interested in applying artificial intelligence methods in creating new technologies for learning and creative professional work. Working through a set of motivating examples from domains such as generative design, dance simulation, social interaction, adaptive user interface design and knowledge sharing in e-learning, the course provides insights on how AI techniques can be used to address important problems in art and design. The topics are presented in a comparative manner to clearly highlight advantages and disadvantages of each method which will provide the students with ability to weight benefits of a particular approach when facing a concrete problem in their research area.

COURSE-LEVEL EDUCATIONAL GOALS:

The course aims to enable students to understand AI in the context of particular problems. Students will be able to distinguish between different epistemological approaches used within AI and select an approach for a specific problem, considering the benefits and limitations of different AI approaches. The course will require students to apply a selected AI technique to their research.  It is recommended that students enrolling in this course have some prior programming experience.

The course will be on the technical/scientific end of the SIAT curriculum. It will review traditional and modern AI approaches, focusing on the algorithms, requirements, benefits and drawbacks. We will use a traditional AI textbook supplemented with papers for more modern deep-learning approaches. Students are expected to work on their projects, applying one or two approaches we covered. Programming tools depend on what the student wants to do. Typically, students pick up the library or tools that are the most suitable for their problem. There are no programming tutorials; students must be able to pick up and apply the tools they need by themselves, creating certain expectations regarding computing proficiency. Contact the instructor if you are not sure about your level of programming skills. 

Grading

  • Critical paper summaries and in-class participation 15%
  • Analysis of a complex problem from the students' research domains with identification of the points where AI techniques are applicable and justifying a selected AI method 20%
  • Research proposal for AI system in the student's research domain and developing a prototype for a small-scale example using AI technique selected 40%
  • Exam 25%

NOTES:


For a pass you need to get at least 50% score for each of the components above.

Materials

MATERIALS + SUPPLIES:

REFERENCE READING:

"Artificial Intelligence:  A Modern Approach" (2021) by Stuart Russell and Peter Norvig; 4th Edition, Prentice Hall  ISBN:9780137505135

The primary readings will be from the textbook. There will be one textbook on a 4-hour loan in the library - this may only be sufficient for a few. SFU does not have an online version. Pearson offers students access to eBook for a per-year fee (57.99); the print version is 245.99. Here is the link to follow: https://www.pearson.com/en-ca/subject-catalog/p/artificial-intelligence-a-modern-approach/P200000003500/9780137505135?utm_source=copystudentlink&utm_medium=referral&utm_campaign=XXLEGP0423PCOM

A collection of research articles complementing the textbook will be introduced during the course.

REQUIRED READING NOTES:

Your personalized Course Material list, including digital and physical textbooks, are available through the SFU Bookstore website by simply entering your Computing ID at: shop.sfu.ca/course-materials/my-personalized-course-materials.

Graduate Studies Notes:

Important dates and deadlines for graduate students are found here: http://www.sfu.ca/dean-gradstudies/current/important_dates/guidelines.html. The deadline to drop a course with a 100% refund is the end of week 2. The deadline to drop with no notation on your transcript is the end of week 3.

Registrar Notes:

ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS

SFU’s Academic Integrity website http://www.sfu.ca/students/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating. Check out the site for more information and videos that help explain the issues in plain English.

Each student is responsible for his or her conduct as it affects the university community. Academic dishonesty, in whatever form, is ultimately destructive of the values of the university. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the university. http://www.sfu.ca/policies/gazette/student/s10-01.html

RELIGIOUS ACCOMMODATION

Students with a faith background who may need accommodations during the term are encouraged to assess their needs as soon as possible and review the Multifaith religious accommodations website. The page outlines ways they begin working toward an accommodation and ensure solutions can be reached in a timely fashion.