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Learning Subgoal Representations with Slow Dynamics

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.

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  • Python 100.0%