How to Implement Decentralized Execution

RLlib
1

Hi all,

This may be a very simple question, but I am having a hard time understanding this. I am following along with the Two-Step Game environment for multi-agent reinforcement learning. I am training with a Centralized Critic with PPO (see: https://github.com/ray-project/ray/blob/master/rllib/examples/centralized_critic.py)

After I train the model, how do I deploy it for execution only? In the same vein, I have also looked at using QMIX (see: https://github.com/ray-project/ray/blob/master/rllib/examples/two_step_game.py) where the agents are grouped during training. Should I ungroup them during execution?

Thanks for the help!

2

Hi! I’m working with Qmix and I have the same question.
Is it possible to make a decentralized explotation of a trained Qmix algorithm?

I don’t find any information about it in the docs or discuss forum. Any ideas are welcome to understand better Qmix algorithm :hugs:

3

Hey, I’m also trying to implement decentralised execution after training my MAPPO policy. Have you managed to figure out how to do it? Thanks

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