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can amp model here reproduce the result of different tasks of ase? #31
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Do you have a video of the behavior from the model? The strike task can be a bit challenging, and the behavior of the model can vary quite a bit between different runs. Have you try just training again? |
here is a demo of location task. I try to train heading, location and strike, the common problem is the "locomotion" skill of these task, just like the demo. amp_task_location-2023-02-20_11.15.21.mp4 |
In principal it should be possible to use AMP for these tasks as well, but I haven't really tried tuning AMP for the tasks in this codebase before. Lookin at the video, it kind of seems like the weigh on the discriminator reward might need to be higher in order to encourage more natural behaviors:
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In my case, higher disc learning rate while lower disc update frequency might help, in addition to balance reward weights. |
Can you show me a copy of your setting? Thank you. |
Maybe |
I also used all motions to train amp location task, but it also didn't work. Have you try it? |
strick.mp4 |
I try to use the following command to train amp model to complete the task just like location
python3 ase/run.py --task HumanoidStrike --cfg_env ase/data/cfg/humanoid_sword_shield_strike.yaml --cfg_train ase/data/cfg/train/rlg/amp_humanoid_task.yaml --motion_file ase/data/motions/reallusion_sword_shield/dataset_strike_amp.yaml
However, the result is worse than which produced by ase. For example, The agent trembles when walking. Do I need to adjust some parameters?
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