LE/EECS 4401 3.0 Artificial Intelligence
GS/EECS 5326 3.0 Topics in Artificial Intelligence
Winter 2021

Department of Electrical Engineering & Computer Science,
York University

Course Project

Proposal (worth 5% of course grade) due: March 9
Presentation (worth 10% of course grade) due: April 6 & 8
Final report (worth 20% of course grade) due: April 13 for EECS4401 and May 3 for EECS5326

This course requires doing a project in the area of artificial intelligence, on a topic related to the material covered in the course. The project may involve doing a literature survey, an evaluation of a an AI solver or tool, an implementation of an AI method, or even a research paper on an AI problem and a proposed solution. Some topics suggestions appear below, classified according to the type of project. Projects in EECS 4401 must be done in teams of two or three students; in EECS 5326, the project must be individual. For team projects, each student must be responsible for a distinct part of the project presentation and a distinct part of the final report, which will be graded separately (the introduction and conclusion of the report can be common).

Project Deliverables

By March 9, you should select a topic and submit a short (one or two pages) project proposal on eClass. The proposal should outline your topic, state the project's objectives, give a tentative timetable for the tasks to be accomplished, and include a list of references (especially important for literature surveys). For implementation projects, it is recommended that a preliminary design for the system be included. You are encouraged to discuss your project with the instructor in advance. You will also get feedback on your proposal.

On April 1, 6, and 8 students will give a short (approx. 15 minutes) class presentation on their project and answer questions (you will be given a time slot in advance).

Your final report on the project is due by April 13 for EECS4401 and April 31 for EECS5326. For literature survey projects, include an overview of the topic area, a discussion of the papers read, and a complete list of references; critical analysis is expected. For system evaluation or implementation projects, state the project's motivation and objectives, provide a readable description the system that was implemented or evaluated, explain how the system is used, describe the testing that was performed, and discuss how usable the system is; include the documented code and/or sample tests in appendix as appropriate. Note that it is not sufficient to simply download a solver and run some of the examples included with it; you must either develop some new examples or evaluate the solver on a wide range of benchmarks.

Suggested Project Topics