Please update the 3d files to your dm_control file.
- To train agents
python train_qua.py pixel_obs=false action_repeat=1 task=quadruped_run agent=ddpg_rotate aug_ratio=4 seed=1agent=hpg
train_xx.py: the run file for each task task=xxx : the task: 1.quadruped_run 2.reacher_hard 3.cheetah_run 4.cheetah3d_run 5.hopper_hop 6.hopper3d_hop 7.Humanoid_stand 8.humanoid_run 9.walker_run 10.walker3d_run agent=xxx: the method you will use: 1.ddpg_our: the original DDPG 2.ddpg_rotate: the DDPG + aug 3.ddpg_rad: DDPG + RAS 4.ddpg_guass: DDPG + GN
aug_ratio: The rotate ratio in the batch 0:no rotate. 1:100% rotate. 2:50% rotate 3:50% rotate 4:25% rotate
The results will be saved at ./exp
The code is adapted from "Continuous MDP Homomorphisms and Homomorphic Policy Gradient" by Sahand Rezaei-Shoshtari, Rosie Zhao, Prakash Panangaden, David Meger, and Doina Precup, presented at the Advances in Neural Information Processing Systems (NeurIPS) conference in 2022. We gratefully acknowledge their significant contributions to this field.