Training from checkpoints / executing trained policies

Hello,

Thank you for the great library!

Is it possible to continue training from checkpoints or executing a trained policy in BenchMARL?

A bit of context: I'm experimenting with policy transfer/reuse across multi-agent teams and would like to test the scenario, when a MARL team kicks-off with a model learned for a related task in the same environment, and adapts it for the target task (i.e. in MPE, reuses the model learned for simple_spread to solve simple_adversary).

Thanks in advance!

No files, tests, or entry points are named in the issue. First map how BenchMARL currently trains policies and handles checkpoints, then determine the expected behavior for resuming training and executing or transferring a trained policy; done requires a documented, tested workflow for these use cases.

Written by the indexing model from the issue text.