What are some simple open problems in multi-agent RL that would be suited for a bachelor's thesis?

Question

I've decided to make my bachelor thesis in RL. I am currently struggling to find a good problem. I am interested in multi-agent RL with the dilemma between selfishness and cooperation.

I only have 2 months to complete this and I'm afraid that multi-agent RL is too difficult and I don't have the knowledge and time to nicely learn this topic.

What are some simple open problems in multi-agent reinforcement learning that would be suited for a bachelor's thesis?

I've only done applied the Q-learning algorithm to solve a text-based environment in OpenAI's gym.

Answer 1

I have several undergraduates working on multiagent deep RL problems for their theses, but most of them have been working for 8-9 months. 2 might be a stretch.

Good multiagent deep RL problems for a bachelor's thesis might look something like:

1. Pick an older video game, which has been studied using Deep RL, but not in depth. Right now my students have been liking Nintendo 64 games.
2. Read the papers that study this game already.
3. Pick one of the described approaches and reproduce the paper's results in your own system.
4. Pick one of the parameters that the paper does not explore changing, and see what happens as you change it.

This probably does not lead to a publishable result, but it is real science and can make for a fine undergraduate thesis.

A slightly harder project, which may require more time, would be to examine the "future work" sections of these papers, and perform one of the experiments suggested there. These experiments often lead to small publishable results.