EXAMPLES.md

Examples

We provide examples to train the following algorithms:

• DQN
• DDPG
• SAC
• REDQ
• PPO

To run these examples, make sure you have installed hydra:

pip install hydra-core

Scripts can be run from the directory of interest using:

python sac.py

or similar. Hyperparameters can be easily changed by providing the arguments to hydra:

python sac.py frames_per_batch=63

Results

Here we can see some results for the SAC and REDQ algorithm. We average the results over 5 different seeds and plot the standard error.

Gym's HalfCheetah-v4

To reproduce a single run:

python sac/sac.py env_name="HalfCheetah-v4" env_task="" env_library="gym"

python redq/redq.py env_name="HalfCheetah-v4" env_task="" env_library="gym"

dm_control's cheetah-run

To reproduce a single run:

python sac/sac.py env_name="cheetah" env_task="run" env_library="dm_control"

python redq/redq.py env_name="cheetah" env_task="run" env_library="dm_control"

Gym's Ant-v4

To reproduce a single run:

python sac/sac.py env_name="Ant-v4" env_task="" env_library="gym"

python redq/redq.py env_name="Ant-v4" env_task="" env_library="gym"

Gym's Walker2D-v4

To reproduce a single run:

python sac/sac.py env_name="Walker2D-v4" env_task="" env_library="gym"

python redq/redq.py env_name="Walker2D-v4" env_task="" env_library="gym"