Multi-agent Reinforcement Learning – PettingZoo

I have a competitive, team-based shooter game that I have converted into a PettingZoo environment. I am now confronting a few issues with this however.

Are there are any good tutorials or libraries which can walk me through using a PettingZoo environment to train a MARL policy? Is there any easy way to implement self-play? (It can be very basic as long as it is present in some capacity) Is there any good way of checking that my PettingZoo env is compliant? Each time I used a different library (ie. TianShou and TorchRL I’ve tried so far), it gives a different error for what is wrong with my code, and each requires the env to be formatted quite differently.

So far I’ve tried following https://pytorch.org/rl/tutorials/multiagent_ppo.html, with both EnvBase in TorchRL and PettingZooWrapper, but neither worked at all. On top of this, I’ve tried https://tianshou.org/en/master/01_tutorials/04_tictactoe.html but modifying it to fit my environment.

By “not working”, I mean that it gives me some vague error that I can’t really fix until I understand what format it wants everything in, but I can’t find good documentation around what each library actually wants.

I definitely didn’t leave my work till last minute. I would really appreciate any help with this, or even a pointer to a library which has slightly clearer documentation for all of this. Thanks!

submitted by /u/SinglePhrase7
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