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Multi-agent reinforcement learning algorithms #7
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rl_games supports MARL.
If you want to use central_value you need to set
for observations. I think if you try to create simple MA env from ant, for example every leg can be agent :) I can help to adapt and test it with rl_games. |
Thanks for your reply and kind advices! I will try to implement this idea in IsaacGym and share further results. I've read the rl_games MARL part code on SMAC env, it supports MARL indeed. But I have 2 further questions on the MARL algorithm implementation of rl_games, based on my code reading and understanding.
Best, |
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Thanks a lot for explanations! I've implemented the MA ant env (each leg corresponds to an agent), however the training result is quite bad for ant, maybe using MAPPO for multi-joints robot control is that suitable? Anyway thanks again! |
Could you try to use central value with a whole observation? |
Hi Denys, actually I used central value for the task however not getting good results, maybe there are some problems in my code and I'm very happy if you could help to check my code. I've forked IsaacGymEnvs and committed my MA_Ant env, you can check this link and test it, the registered env task name is MA_Ant. Apart from the new env class ma_ant, there are also 2 changes in the original IsaacGymEnvs repo:
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Thanks, Ill play with it tomorrow evening. |
The best reward of MA_Ant is below 10 (Ant env is around 4k), but I did not fine-tune training parameters used in MA_Ant, so I don't whether there are some problems in my code, or it's just not suitable to consider each leg as an agent in MAPPO. |
@reso1 I've found bug in your code:
And I added one more change to the compute_ant_observations:
So legs see a little bit different observations, I think it is not a must for your case but without it maximum reward was 2000. |
Cool, thanks for your kind help! BTW, if you have any plan on formally integrating MARL on IsaacGym using rl_games, I'm very glad to help it :) |
Hi Bryan, the following is the pointer to the MA ant repo, you can check
the closed issue in IsaacGymEnvs where I mentioned details about this
environment.
https://github.com/reso1/IsaacGymEnvs
Enjoy!
Bryan Chen ***@***.***> 于2021年12月18日周六 10:41写道:
… Hi @reso1 <https://github.com/reso1>, could you please give me some
pointers if I wanted to fork your MA ant repo to add a simple mat to the
environment? In particular I would like to recreate the RoboSumo
environment https://github.com/openai/robosumo . Thank you!
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Hi ~ Are you going to share the repo? I am excited to play with it:D |
I'm trying to use Isaac Gym for multi-agent reinforcement learning (MARL), is there any future plan on this?
If not, can you give any suggestions on how should I integrate MARL algorithms into Issac Gym? Should I start from rl_games repo or maybe integrate other MARL-supported repos?
Thanks for your help!
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