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6.S890 | Fall 2024 | Graduate

# Topics in Multiagent Learning

This course includes a project presentation. Projects may be done individually or in groups of 2–3 students and can be theoretical or experimental.

To get started, here are several project ideas. These include two empirical challenges—Phantom Tic-Tac-Toe and Team Poker—as well as some theoretical ideas. Feel free to choose any of these for your course project, or propose an alternative that interests you. If you’re deciding between Phantom Tic-Tac-Toe and Team Poker, we recommend selecting Phantom Tic-Tac-Toe, as coordinating a team in Team Poker can be notoriously tricky to manage.

- MIT 6.S890 Phantom Tic-Tac-Toe Challenge
  Please note: additional referenced files are not available to OCW users.
- MIT 6.S890 Team Leduc Poker Challenge
  Please note: additional referenced files are not available to OCW users.
- MIT 6.S890 Additional Projects Ideas

Each student or team will need to present their projects at the end of the semester. Each team will have 6 minutes for their presentation, plus 1–2 minutes for questions. For teams with more than one member, feel free to organize the presentation as you prefer: each one speaking about a different aspect, only one speaker, etc. The goal of the presentation is to give us and the other people in the class an overview of the cool approaches you attempted and the main highlights.

The submission deadline for the final report is the last day of class. There is no strict page limit. However, please make sure to address (at least) the following:

- What project did you work on? What were the technical challenges?
- How did you split the work among the team members?
- What approach did you use?
- How did you evaluate your approach? For the Phantom Tic-Tac-Toe challenges, it is acceptable to refer to the leaderboard.
- What were the results? How does the performance compare to other approaches (if applicable)? Are the results surprising or expected?
- What were the bottlenecks of the approach you selected? What future work could be done to overcome them?
- What are the main takeaways of your project?

## Course Info

##### Instructor

- Prof. Gabriele Farina

##### Departments

- Electrical Engineering and Computer Science

##### As Taught In

Fall 2024

##### Level

Graduate

##### Topics

- Engineering
  - Computer Science
    - Artificial Intelligence

##### Learning Resource Types

notes Lecture Notes
assignment_turned_in Problem Set Solutions
assignment Problem Sets
group_work Projects
auto_stories Readings

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