pysc2 VS stable-baselines

Good evening, guys. I currently use StarCraft 2 as a tool for experimenting with my deep reinforcement learning projects, I have also used OpenAI Gym.

DRL experiments using StarCraft II Learning Environment.

If you are looking to develop a machine-learning based bot you can go with pysc2: https://github.com/deepmind/pysc2

in terms of deepmind: https://github.com/deepmind/pysc2 source code if you want to take a look.

As underlined by gold-panda, you can give a try with multiprocessing. I once implemented a version based on what is done in stable_baselines v1 (https://github.com/hill-a/stable-baselines/blob/master/stable_baselines/common/vec_env/subproc_vec_env.py)

Found relevant code at https://github.com/hill-a/stable-baselines + all code implementations here

Depends what you wanna do. Universal answer would be https://stable-baselines.readthedocs.io/

As you will see here it is recommended to augment this safety measure with target kl_divergence, that will ensure even smoother learning and enforce early stopping to prevent learning collapses.

Code for https://arxiv.org/abs/1707.06347 found: https://github.com/hill-a/stable-baselines

I haven't read the code, but stable-baselines doesn't support multi-agent environments (https://github.com/hill-a/stable-baselines/issues/423), so I think they're trying to make learning multi-agent easier with Environment.train().

- https://github.com/hill-a/stable-baselines (Tensorflow)

- tf2 speed: https://github.com/hill-a/stable-baselines/issues/576#issuecomment-573331715