We propose a slowness objective to effectively learn the subgoal representation for goal-conditioned hierarchical reinforcement learning. Our paper is accepted by ICLR 2021.
The python dependencies are as follows.
Run the codes with python train_hier_sac.py. The tensorboard files are saved in the runs folder and the
trained models are saved in the saved_models folder.