Balancing Exploration and Exploitation in Hierarchical Reinforcement Learning via Latent Landmark Graphs

Table of Contents

• Install
• Usage
• Future works

Install

• Python $\geq$ 3.6
• PyTorch == 1.4.0
• gym==0.10.5
• Mujoco210
• Mujoco-py<2.2,>=2.1

Usage

We provide the training scripts in HILL/run.sh.

The parameter setting can be found in HILL/arguments.

Running example

python train_hier_sac.py --c 50 --abs_range 20 --env-name AntMaze1Test-v1 --test AntMaze1Test-v3

Results of the running example (random seeds). The $x$-axis shows the epochs of training, and the y-axis shows the average success rate over $10$ episodes.

Future works

• learn a world model for better planning