Code for our NeurIPS 2020 paper "PlanGAN"
Requirements:
- Mujoco-py
- PyTorch
- NumPy
- SkLearn
- Joblib
To train an agent on FetchPickAndPlace run:
python train.py --env="fetch_push" --expt_name="FetchPush"
Pre-trained agents for FetchPush and FetchPickAndPlace are included in this repo. They can be evaluated with:
python evaluate.py --expt_name="FetchPickAndPlace" --num_trajectories=50
We also include a Jupyter notebook that allows you to visualise the imagined trajectories that the GANs generate (visualise_trajectories.ipynb).
Note that the exact hyperparameters used for the reported FetchPush and FetchPickAndPlace experiments are saved in JSON files located in the experiments folder.