Comments (5)
PaParaZz1
commented on May 29, 2024
1
Naive PPO and self-play PPO have worked well in #23, and we will push league demo in the following PR.
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PaParaZz1
commented on May 29, 2024
1
@PaParaZz1 Could you please create an issue for the following PR?
ok I will create a new issue about league training for slime volleyball env this Tuesday.
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PaParaZz1
commented on May 29, 2024
@LuciusMos PPO(with RNN and without RNN), on policy training, slimeVolley-v0 env
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zxzzz0
commented on May 29, 2024
To clarify let's use league training with 3 roles (MA, ME, LE) rather than pure self-play training. There is also a built-in AI and do not use that for training. After training is finished we can evaluate agents against built-in AI and compare the numeric numbers with the report above.
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zxzzz0
commented on May 29, 2024
@PaParaZz1 Could you please create an issue for the following PR?
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Related Issues (20)
- Question about MBPO. HOT 5
- Document about config HOT 6
- wandb crash HOT 1
- Env manager is closed after wandb logger is set HOT 2
- `enable_save_figure()` has no detailed document, and its comment is wrong. HOT 4
- Does model support multiple input parameters? HOT 1
- evaluate on same env for multiple time after fails HOT 4
- `GAIL` the algorithm performs much worse than from its original paper. HOT 6
- Setting of Parameters in gym_anytrading and How to Evaluate Training Performance HOT 3
- Halfcheetah has negative state in z position HOT 2
- Error occurs when async_mode=True in example/ppo.py HOT 3
- Error occurs when running in parallel HOT 2
- NameNotFound: Environment stocks doesn't exist. HOT 11
- not compatible with gym_pybullet_drones env HOT 5
- how to use logger HOT 2
- why no tanh after sample action in ppo HOT 4
- entry_points() got an unexpected keyword argument 'group' HOT 1
- ram usage increase overtime HOT 1
- Trading deploy - issues when trying to process a single window HOT 5
- how to separate training environments and evaluation environments HOT 1
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