PyTorch implementation of "Improving Generalization in Meta-RL with Imaginary Tasks from Latent Dynamics Mixture", NeurIPS2021.
Our code is based on the reference implementation of variBAD.
Refer to the requirements in https://github.com/lmzintgraf/varibad.
You don't need MuJoCo license to run the gridworld experiment.
python main.py --env-type gridworld_ldm
python main.py --env-type mujoco_ant_dir_ldm
python main.py --env-type mujoco_ant_goal_ldm
python main.py --env-type mujoco_cheetah_vel_ldm
If you want to run rl2 and varibad,
python main.py --env-type (envname)_rl2
python main.py --env-type (envname)_varibad
Evaluation results will be stored in the logs folder
If you want to change the configurations of LDM, refer to configurations in the config folder
The major part of the algorithm is in metalearner_ldm.py.