In my opinion, the best way to do a grad-level project course is to use it as an opportunity to make progress on research on a related topic, especially if it aligns with your existing research agenda. I see the best outcome of the course as you getting as close to producing a publishable research artifact as possible, given the timeframe of the course. With that in mind, you will be expected to submit a 6-9-page research paper (following the ICML 2026 style guide) and give a presentation on your work. Note that the ICML submission deadline is typically the end of January, giving you a chance to turn your class paper into a real submission to ICML.
That said, we don’t require you to produce an ICML-tier publication in 10 weeks. The goal is for you to get research experience on a topic that you’re excited about which relates to the course. Expectations for the novelty, significance, and scale of the contribution and results of your paper will be scaled back dramatically relative to a full AI conference paper, and are more akin to a workshop paper. As examples of smaller-scale projects that would fit with the class, you could start with replicating an existing method, and apply it to a new experimental domain or dataset. You could try applying your favorite single-agent RL method in a multi-agent setting, and see if it needs any modifications to allow it to work.
Note that it is totally acceptable, and in fact ideal, if your normal research aligns with the class, and you can continue making progress on your research agenda and write up the results for the class project. You are also encouraged to form groups of up to four students for the project. Through these avenues, you may be able to tackle more challenging research problems with more novelty, such as developing a new algorithm or technique. We encourage you to pursue this if you think it’s possible!
Just like a real Call for Papers (CfP), here is a list of suggested topics appropriate for the class project:
If you would like to do a project on a topic you think is related that you don’t see listed here, please contact us.
Criteria Your paper will be evaluated similarly to how research papers are evaluated for conferences: on the novelty, significance, soundness of the experimental or theoretical results, writing/presentation, and coverage of the related work. However, the degree of novelty, significance, etc. is expected to be less than a full conference paper (more similar to a workshop paper).
For all project deliverables, only one member should submit on Gradescope on behalf of the entire group. Please list all group members in your submission. The same member should consistently be the one submitting for the group.
Proposal (5% of total grade, due 11:59pm October 17)
Presentation (10% of total grade, due in class on Dec 3 or 5)
Writeup (35% of total grade, due 11:59pm Dec 1) Please submit a 6-9 page paper structured like a typical research paper, following the ICML style guidelines (page limit applies only to the content, not the references or appendices). Suggested sections include the abstract, introduction, related work, (optional: technical preliminaries, which explain the technical details behind existing methods that your work builds on), methods (the technical details of what you’re proposing), experiments (describing the experiments you will run, environments you used), results, and conclusion/discussion. These are not a hard requirement; you may also have theoretical results you wish to include. Note also that this standard format can sometimes be tweaked effectively.
At the end of your writeup, include a brief Statement of Contributions section that details the contributions made by each group member (for an example see p. 16 of this paper). This section does not count towards the page limit.
Create a github repository for any code related to your project, and include a link to the repo in your paper (if you are submitting the same paper to ICML, remember to anonymize or remove this link!). The repository should include all relevant code needed to reproduce the results. It should also come with a README file documenting what commands you ran.
Note that your submission should not be anonymized, and should include group member’s names as authors. This is because we will scale expectations down for papers with fewer authors, so reviewers need to know how many authors contributed to the paper.
Students are encouraged to form groups of up to 4 students. The expectations for the project will scale with the number of students, such that projects with more students are expected to be more impactful. To be concrete, we expect roughly that the length of the report should also scale with the number of students:
It’s okay to go over these heuristic limits, but do not submit a report longer than 9 pages for any group size. Please include a statement of contributions in the appendix of the paper describing what each person did. However, don’t be discouraged from teaming up into groups! In the ideal case, you can aim to write an impactful research paper that could potentially be submitted to ICML, and you may need more students to pull this off.
If you're looking to find teammates to work on your project idea, or join someone else's team, consider using this project matching spreadsheet.
Students working with a research lab can use their lab resources, if feasible. Otherwise, options include:
Please approach the instructor in-case the available compute is a bottleneck for your projects.
For your paper, you may want to run experiments using multi-agent environments. For an informal list of such environments, please see this doc of possible multi-agent environments. If you have ideas for further environments or datasets, feel free to leave a comment suggesting them.